phd aims

Research Aims, Objectives & Questions

The “Golden Thread” Explained Simply (+ Examples)

By: David Phair (PhD) and Alexandra Shaeffer (PhD) | June 2022

The research aims , objectives and research questions (collectively called the “golden thread”) are arguably the most important thing you need to get right when you’re crafting a research proposal , dissertation or thesis . We receive questions almost every day about this “holy trinity” of research and there’s certainly a lot of confusion out there, so we’ve crafted this post to help you navigate your way through the fog.

Overview: The Golden Thread

• What is the golden thread
• What are research aims ( examples )
• What are research objectives ( examples )
• What are research questions ( examples )
• The importance of alignment in the golden thread

What is the “golden thread”?  

The golden thread simply refers to the collective research aims , research objectives , and research questions for any given project (i.e., a dissertation, thesis, or research paper ). These three elements are bundled together because it’s extremely important that they align with each other, and that the entire research project aligns with them.

Importantly, the golden thread needs to weave its way through the entirety of any research project , from start to end. In other words, it needs to be very clearly defined right at the beginning of the project (the topic ideation and proposal stage) and it needs to inform almost every decision throughout the rest of the project. For example, your research design and methodology will be heavily influenced by the golden thread (we’ll explain this in more detail later), as well as your literature review.

The research aims, objectives and research questions (the golden thread) define the focus and scope ( the delimitations ) of your research project. In other words, they help ringfence your dissertation or thesis to a relatively narrow domain, so that you can “go deep” and really dig into a specific problem or opportunity. They also help keep you on track , as they act as a litmus test for relevance. In other words, if you’re ever unsure whether to include something in your document, simply ask yourself the question, “does this contribute toward my research aims, objectives or questions?”. If it doesn’t, chances are you can drop it.

Alright, enough of the fluffy, conceptual stuff. Let’s get down to business and look at what exactly the research aims, objectives and questions are and outline a few examples to bring these concepts to life.

Research Aims: What are they?

Simply put, the research aim(s) is a statement that reflects the broad overarching goal (s) of the research project. Research aims are fairly high-level (low resolution) as they outline the general direction of the research and what it’s trying to achieve .

Research Aims: Examples  

True to the name, research aims usually start with the wording “this research aims to…”, “this research seeks to…”, and so on. For example:

“This research aims to explore employee experiences of digital transformation in retail HR.”   “This study sets out to assess the interaction between student support and self-care on well-being in engineering graduate students”  

As you can see, these research aims provide a high-level description of what the study is about and what it seeks to achieve. They’re not hyper-specific or action-oriented, but they’re clear about what the study’s focus is and what is being investigated.

Need a helping hand?

Research Objectives: What are they?

The research objectives take the research aims and make them more practical and actionable . In other words, the research objectives showcase the steps that the researcher will take to achieve the research aims.

The research objectives need to be far more specific (higher resolution) and actionable than the research aims. In fact, it’s always a good idea to craft your research objectives using the “SMART” criteria. In other words, they should be specific, measurable, achievable, relevant and time-bound”.

Research Objectives: Examples  

Let’s look at two examples of research objectives. We’ll stick with the topic and research aims we mentioned previously.  

For the digital transformation topic:

To observe the retail HR employees throughout the digital transformation. To assess employee perceptions of digital transformation in retail HR. To identify the barriers and facilitators of digital transformation in retail HR.

And for the student wellness topic:

To determine whether student self-care predicts the well-being score of engineering graduate students. To determine whether student support predicts the well-being score of engineering students. To assess the interaction between student self-care and student support when predicting well-being in engineering graduate students.

  As you can see, these research objectives clearly align with the previously mentioned research aims and effectively translate the low-resolution aims into (comparatively) higher-resolution objectives and action points . They give the research project a clear focus and present something that resembles a research-based “to-do” list.

Research Questions: What are they?

Finally, we arrive at the all-important research questions. The research questions are, as the name suggests, the key questions that your study will seek to answer . Simply put, they are the core purpose of your dissertation, thesis, or research project. You’ll present them at the beginning of your document (either in the introduction chapter or literature review chapter) and you’ll answer them at the end of your document (typically in the discussion and conclusion chapters).  

The research questions will be the driving force throughout the research process. For example, in the literature review chapter, you’ll assess the relevance of any given resource based on whether it helps you move towards answering your research questions. Similarly, your methodology and research design will be heavily influenced by the nature of your research questions. For instance, research questions that are exploratory in nature will usually make use of a qualitative approach, whereas questions that relate to measurement or relationship testing will make use of a quantitative approach.  

Let’s look at some examples of research questions to make this more tangible.

Research Questions: Examples  

Again, we’ll stick with the research aims and research objectives we mentioned previously.  

For the digital transformation topic (which would be qualitative in nature):

How do employees perceive digital transformation in retail HR? What are the barriers and facilitators of digital transformation in retail HR?  

And for the student wellness topic (which would be quantitative in nature):

Does student self-care predict the well-being scores of engineering graduate students? Does student support predict the well-being scores of engineering students? Do student self-care and student support interact when predicting well-being in engineering graduate students?  

You’ll probably notice that there’s quite a formulaic approach to this. In other words, the research questions are basically the research objectives “converted” into question format. While that is true most of the time, it’s not always the case. For example, the first research objective for the digital transformation topic was more or less a step on the path toward the other objectives, and as such, it didn’t warrant its own research question.  

So, don’t rush your research questions and sloppily reword your objectives as questions. Carefully think about what exactly you’re trying to achieve (i.e. your research aim) and the objectives you’ve set out, then craft a set of well-aligned research questions . Also, keep in mind that this can be a somewhat iterative process , where you go back and tweak research objectives and aims to ensure tight alignment throughout the golden thread.

The importance of strong alignment 

Alignment is the keyword here and we have to stress its importance . Simply put, you need to make sure that there is a very tight alignment between all three pieces of the golden thread. If your research aims and research questions don’t align, for example, your project will be pulling in different directions and will lack focus . This is a common problem students face and can cause many headaches (and tears), so be warned.

Take the time to carefully craft your research aims, objectives and research questions before you run off down the research path. Ideally, get your research supervisor/advisor to review and comment on your golden thread before you invest significant time into your project, and certainly before you start collecting data .  

Recap: The golden thread

In this post, we unpacked the golden thread of research, consisting of the research aims , research objectives and research questions . You can jump back to any section using the links below.

As always, feel free to leave a comment below – we always love to hear from you. Also, if you’re interested in 1-on-1 support, take a look at our private coaching service here.

Psst... there’s more!

This post was based on one of our popular Research Bootcamps . If you're working on a research project, you'll definitely want to check this out ...

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39 Comments

Thank you very much for your great effort put. As an Undergraduate taking Demographic Research & Methodology, I’ve been trying so hard to understand clearly what is a Research Question, Research Aim and the Objectives in a research and the relationship between them etc. But as for now I’m thankful that you’ve solved my problem.

Well appreciated. This has helped me greatly in doing my dissertation.

An so delighted with this wonderful information thank you a lot.

so impressive i have benefited a lot looking forward to learn more on research.

I am very happy to have carefully gone through this well researched article.

Infact,I used to be phobia about anything research, because of my poor understanding of the concepts.

Now,I get to know that my research question is the same as my research objective(s) rephrased in question format.

I please I would need a follow up on the subject,as I intends to join the team of researchers. Thanks once again.

Thanks so much. This was really helpful.

I know you pepole have tried to break things into more understandable and easy format. And God bless you. Keep it up

i found this document so useful towards my study in research methods. thanks so much.

This is my 2nd read topic in your course and I should commend the simplified explanations of each part. I’m beginning to understand and absorb the use of each part of a dissertation/thesis. I’ll keep on reading your free course and might be able to avail the training course! Kudos!

Thank you! Better put that my lecture and helped to easily understand the basics which I feel often get brushed over when beginning dissertation work.

This is quite helpful. I like how the Golden thread has been explained and the needed alignment.

This is quite helpful. I really appreciate!

The article made it simple for researcher students to differentiate between three concepts.

Very innovative and educational in approach to conducting research.

I am very impressed with all these terminology, as I am a fresh student for post graduate, I am highly guided and I promised to continue making consultation when the need arise. Thanks a lot.

A very helpful piece. thanks, I really appreciate it .

Very well explained, and it might be helpful to many people like me.

Wish i had found this (and other) resource(s) at the beginning of my PhD journey… not in my writing up year… 😩 Anyways… just a quick question as i’m having some issues ordering my “golden thread”…. does it matter in what order you mention them? i.e., is it always first aims, then objectives, and finally the questions? or can you first mention the research questions and then the aims and objectives?

Thank you for a very simple explanation that builds upon the concepts in a very logical manner. Just prior to this, I read the research hypothesis article, which was equally very good. This met my primary objective.

My secondary objective was to understand the difference between research questions and research hypothesis, and in which context to use which one. However, I am still not clear on this. Can you kindly please guide?

In research, a research question is a clear and specific inquiry that the researcher wants to answer, while a research hypothesis is a tentative statement or prediction about the relationship between variables or the expected outcome of the study. Research questions are broader and guide the overall study, while hypotheses are specific and testable statements used in quantitative research. Research questions identify the problem, while hypotheses provide a focus for testing in the study.

Exactly what I need in this research journey, I look forward to more of your coaching videos.

This helped a lot. Thanks so much for the effort put into explaining it.

What data source in writing dissertation/Thesis requires?

What is data source covers when writing dessertation/thesis

This is quite useful thanks

I’m excited and thankful. I got so much value which will help me progress in my thesis.

where are the locations of the reserch statement, research objective and research question in a reserach paper? Can you write an ouline that defines their places in the researh paper?

Very helpful and important tips on Aims, Objectives and Questions.

Thank you so much for making research aim, research objectives and research question so clear. This will be helpful to me as i continue with my thesis.

Thanks much for this content. I learned a lot. And I am inspired to learn more. I am still struggling with my preparation for dissertation outline/proposal. But I consistently follow contents and tutorials and the new FB of GRAD Coach. Hope to really become confident in writing my dissertation and successfully defend it.

As a researcher and lecturer, I find splitting research goals into research aims, objectives, and questions is unnecessarily bureaucratic and confusing for students. For most biomedical research projects, including ‘real research’, 1-3 research questions will suffice (numbers may differ by discipline).

Awesome! Very important resources and presented in an informative way to easily understand the golden thread. Indeed, thank you so much.

Well explained

The blog article on research aims, objectives, and questions by Grad Coach is a clear and insightful guide that aligns with my experiences in academic research. The article effectively breaks down the often complex concepts of research aims and objectives, providing a straightforward and accessible explanation. Drawing from my own research endeavors, I appreciate the practical tips offered, such as the need for specificity and clarity when formulating research questions. The article serves as a valuable resource for students and researchers, offering a concise roadmap for crafting well-defined research goals and objectives. Whether you’re a novice or an experienced researcher, this article provides practical insights that contribute to the foundational aspects of a successful research endeavor.

A great thanks for you. it is really amazing explanation. I grasp a lot and one step up to research knowledge.

I really found these tips helpful. Thank you very much Grad Coach.

I found this article helpful. Thanks for sharing this.

thank you so much, the explanation and examples are really helpful

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How to write a successful research proposal

As the competition for PhD places is incredibly fierce, your research proposal can have a strong bearing on the success of your application - so discover how to make the best impression

What is a research proposal?

Research proposals are used to persuade potential supervisors and funders that your work is worthy of their support. These documents setting out your proposed research that will result in a Doctoral thesis are typically between 1,500 and 3,000 words in length.

Your PhD research proposal must passionately articulate what you want to research and why, convey your understanding of existing literature, and clearly define at least one research question that could lead to new or original knowledge and how you propose to answer it.

Professor Leigh Wilson, director of the graduate school at the University of Westminster, explains that while the research proposal is about work that hasn't been done yet, what prospective supervisors and funders are focusing on just as strongly is evidence of what you've done - how well you know existing literature in the area, including very recent publications and debates, and how clearly you've seen what's missing from this and so what your research can do that's new. Giving a strong sense of this background or frame for the proposed work is crucial.

'Although it's tempting to make large claims and propose research that sweeps across time and space, narrower, more focused research is much more convincing,' she adds. 'To be thorough and rigorous in the way that academic work needs to be, even something as long as a PhD thesis can only cover a fairly narrow topic. Depth not breadth is called for.'

The structure of your research proposal is therefore important to achieving this goal, yet it should still retain sufficient flexibility to comfortably accommodate any changes you need to make as your PhD progresses.

Layout and formats vary, so it's advisable to consult your potential PhD supervisor before you begin. Here's what to bear in mind when writing a research proposal.

Your provisional title should be around ten words in length, and clearly and accurately indicate your area of study and/or proposed approach. It should be catchy, informative and interesting.

The title page should also include personal information, such as your name, academic title, date of birth, nationality and contact details.

Aims and objectives

This is a short summary of your project. Your aims should be two or three broad statements that emphasise what you ultimately want to achieve, complemented by several focused, feasible and measurable objectives - the steps that you'll take to answer each of your research questions. This involves clearly and briefly outlining:

• how your research addresses a gap in, or builds upon, existing knowledge
• how your research links to the department that you're applying to
• the academic, cultural, political and/or social significance of your research questions.

Literature review

This section of your PhD proposal discusses the most important theories, models and texts that surround and influence your research questions, conveying your understanding and awareness of the key issues and debates.

It should focus on the theoretical and practical knowledge gaps that your work aims to address, as this ultimately justifies and provides the motivation for your project.

Methodology

Here, you're expected to outline how you'll answer each of your research questions. A strong, well-written methodology is crucial, but especially so if your project involves extensive collection and significant analysis of primary data.

In disciplines such as humanities the research proposal methodology identifies the data collection and analytical techniques available to you, before justifying the ones you'll use in greater detail. You'll also define the population that you're intending to examine.

You should also show that you're aware of the limitations of your research, qualifying the parameters that you plan to introduce. Remember, it's more impressive to do a fantastic job of exploring a narrower topic than a decent job of exploring a wider one.

Concluding or following on from your methodology, your timetable should identify how long you'll need to complete each step - perhaps using bi-weekly or monthly timeslots. This helps the reader to evaluate the feasibility of your project and shows that you've considered how you'll go about putting the PhD proposal into practice.

Bibliography

Finally, you'll provide a list of the most significant texts, plus any attachments such as your academic CV . Demonstrate your skills in critical reflection by selecting only those resources that are most appropriate.

Final checks

Before submitting this document along with your PhD application, you'll need to ensure that you've adhered to the research proposal format. This means that:

• every page is numbered
• it's professional, interesting and informative
• the research proposal has been proofread by both an experienced academic (to confirm that it conforms to academic standards) and a layman (to correct any grammatical or spelling errors)
• it has a contents page
• you've used a clear and easy-to-read structure, with appropriate headings.

Research proposal examples

To get a better idea of how your PhD proposal may look, some universities have provided examples of research proposals for specific subjects:

• The Open University - Social Policy and Criminology
• University of Sheffield - Sociological Studies
• University of Sussex
• University of York - Politics

Find out more

• Explore PhD studentships .
• For tips on writing a thesis, see 7 steps to writing a dissertation .
• Read more about PhD study .

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• CAREER COLUMN
• 06 November 2018

Twenty things I wish I’d known when I started my PhD

• Lucy A. Taylor 0

Lucy A. Taylor earned her zoology PhD from the University of Oxford, UK. She is now a postdoctoral researcher at Save the Elephants in Nairobi, Kenya, and a visiting researcher in the Department of Zoology at Oxford.

You can also search for this author in PubMed   Google Scholar

Starting a PhD can be tough. Looking back, there are many things I wish I’d known at the beginning. Here, I have curated a list of advice from current PhD students and postdoctoral researchers from the Department of Zoology at my institution, the University of Oxford, UK, to aid new graduate students.

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This is an article from the Nature Careers Community, a place for Nature readers to share their professional experiences and advice. Guest posts are encouraged. You can get in touch with the editor at [email protected].

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What is a PhD?

• Types of Doctorates
• A Doctor of Philosophy (PhD) is the highest globally recognized postgraduate degree that higher education institutions can award.
• PhDs are awarded to candidates who undertake original and extensive research in a particular field of study.
• Full time PhD programmes typically last three to four years, whilst part time PhD programmes typically last six to seven years.
• A PhD can lead to an academia teaching role or a career in research. A PhD can also equip you with skills suitable for a wide range of jobs unrelated to your research topic or academia.

Definition of a PhD – A Doctor of Philosophy (commonly abbreviated to PhD , Ph.D or a DPhil ) is a university research degree awarded from across a broad range of academic disciplines; in most countries, it is a terminal degree, i.e. the highest academic degree possible.

PhDs differ from undergraduate and master’s degrees in that PhDs are entirely research-based rather than involving taught modules (although doctoral training centres (DTCs) offer programmes that start with a year of lecture-based teaching to help develop your research skills prior to starting your project).

In most English-speaking countries, those that complete a PhD use the title “Doctor” (typically abbreviated to Dr) in front of their names and are referred to as such within academic and/or research settings. Those that work in fields outside of academia may decide not to use the formal doctor title but use post-nominal letters (e.g. John Smith PhD); it’s unusual though for someone to use both the Doctor title and post-nominal letters in their name.

PhD vs Doctorate

A PhD and a professional doctorate are both research-based terminal degrees.

However, where a PhD focuses on original research mostly around theoretical concepts, a professional doctorate focuses on examining existing knowledge to solve real-life, practical problems.

While there is much crossover between the two, a PhD is generally better suited for an individual to wants to advance the knowledge and understanding in their field, and a professional doctorate degree is better suited to a working professional who wants to better be able to apply knowledge and understanding to their field.

What Are the Entry Requirements for a PhD?

To be accepted on to a PhD programme, students usually need to hold at least a high ( 2:1 and above ) undergraduate degree that is related to the field of research that they want to pursue. A PhD candidate may also be expected to hold a Master’s degree , however, this does not mean you must have one, as it is still possible to enrol into a PhD without a Master’s .

Self-funded courses may sometimes be more relaxed in relation to entry requirements. It may be possible to be accepted onto a self-funded PhD programme with lower grades, though these students typically demonstrate their suitability for the role through professional work experience.

Whilst a distance learning project is possible , most PhD candidates will carry out their research over at least three years based at their university, with regular contact with two academic supervisors (primary and secondary). This is particularly the case for lab-based projects, however, some PhD projects require spending time on-site away from university (e.g. at a specialist research lab or at a collaborating institution abroad).

How Long Does a PhD Take?

Typically, full-time PhDs last 3-4 years and part-time PhDs last 6-7 years. However, at the discretion of the university, the thesis writing-up period can be extended by up to four years.

Although most doctoral programmes start in September or October, they are generally much more flexible than taught-courses and can start at any time of the year.

How Much Does a PhD Cost?

Tuition fees for UK and EU students vary between £3,000 and £6,000 per year, with the average tuition fee of £4,712 per year for 2023/24 programmes.

Tuition fees increase considerably for international students, varying between £16,000 to £25,000 per year, with an average tuition fee of £19,600 per year .

Nonetheless, most students will secure PhD funding in the form of studentships, scholarships and bursaries to help pay for these fees. These funding opportunities can either be partial, which cover tuition fees only, or full, which cover both tuition fees and living expenses.

UK national students can also apply for Doctoral Loans from Student Finance England if they are unable to secure funding.

Finding a PhD has never been this easy – search for a PhD by keyword, location or academic area of interest.

What Does a PhD Involve?

To be awarded a PhD, a doctoral student is required to produce a substantial body of work that adds new knowledge to their chosen field.

A PhD programme will typically involve four key stages:

Stage 1: Literature Review

The first year of a PhD involves attending regular meetings with your supervisors and carrying out a search on previously published work in your subject area. This search will be used to produce a literature review which should set the context of the project by explaining the foundation of what is currently known within the field of research, what recent developments have occurred, and where the gaps in knowledge are. In most cases, this will be an extension of your research proposal should you have produced one as part of your application. The literature review should conclude by outlining the overarching aims and objectives of the research project. This stage of setting achievable goals which are original and contribute to the field of research is an essential first step in a successful PhD.

The supervisor is the main point of contact through the duration of a PhD – but remember: they are there to mentor, not to teach, or do it for you . It will be your responsibility to plan, execute and monitor your own work as well as to identify gaps in your own knowledge and address them.

Stage 2: Research

The second year (and prehapse some of your third year) is when you work on your research. Having identified novel research questions from your review of the literature, this is where you collect your data to help answer these questions. How you do this will depend on the nature of your doctoral research: for example, you may design and run experiments in a lab alongside other PhD students or visit excavation sites in remote regions of the world. You should check in regularly with your supervisors to update them and run any ideas or issues past them.

Have the structure and chapters of your thesis in mind as you develop and tackle your research questions. Working with a view of publishing your work will be very valuable later on.

Stage 3: Write up of Thesis

The next key stage of a PhD is writing a doctoral thesis , which typically takes from anywhere between three months to one year. A thesis is a substantial body of work that describes the work and outcomes of the research over the previous two to three years. It should tell a detailed story of the PhD project – focusing on:

• The motivations for the research questions identified from the literature review.
• The methodologies used, results obtained, and a comprehensive analysis and discussion of the findings.
• A detailed discussion of the key findings with an emphasis on the original contributions made to your field of research and how this has been impactful.

There is no universal rule for the length of a PhD thesis, but general guidelines set the word count between 80,000 to 100,000 words.

For your thesis to be successful, it needs to adequately defend your argument and provide a unique or increased insight into your field that was not previously available.

Stage 4: Attending the Viva

A viva voce , most commonly referred to as just a ‘ viva ‘, is an interview-style examination where the PhD student is required to engage in a critical appraisal of their work and defend their thesis against at least two examiners. The examiners will ask questions to check the PhD student has an in-depth understanding of the ideas and theories proposed in their thesis, and whether they have developed the research skills that would be expected of them.

The viva is one of the final steps in achieving a PhD, and typically lasts at least two hours, but this duration can vary depending on the examiners, the university and the PhD project itself.

Once you have done the viva – you’re on the home stretch. You will typically be asked to make some amendments to your thesis based on the examiner’s feedback. You are then ready to submit your final thesis for either:

• PhD – If you pass the requirements you will be awarded a PhD degree (most common outcome),
• MPhil – If you failed to meet requirements for a PhD, you may be downgraded to an MPhil degree (uncommon outcome),
• Fail – No award is given, typically for cases of plagiarism (extremely uncommon outcome).

What Is It Like to Undertake a PhD?

We’re often asked what it is like to undertake a PhD study. Unfortunately, this isn’t a simple answer to this question as every research project is different.

To help give insight into the life of a PhD student, we’ve interviewed PhD students at various stages of their programmes and put together a series of PhD Student Interviews . Check out the link to find out what a PhD is like and what advice they have to offer you.

What Are the Benefits of A PhD?

A PhD is the highest globally recognised postgraduate degree that higher education institutions can award. The degree, which is awarded to candidates who demonstrate original and independent research in a particular field of study, is not only invaluable in itself, but sets you up with invaluable skills and traits.

Career Opportunities

First, a PhD prepares you for a career in academia if you wish to continue in this area. This takes form as a career in the Higher Education sector, typically as a lecturer working their way to becoming a professor leading research on the subject you’ve studied and trained in.

Second, a PhD also enables the opportunity for landing a job in a research & development role outside of the academic environment. Examples of this include laboratory work for a private or third sector company, a governmental role and research for commercial and industrial applications.

Transferable Skills

Finally, in possessing a PhD degree, you can show to employers that you have vital skills that make you an asset to any company. Three examples of the transferable skills that you gain through a PhD are effective communication, time management, and report writing.

• Communication – presenting your work in written and oral forms using journal papers and podium presentations, shows your ability to share complex ideas effectively and to those with less background knowledge than you. Communication is key in the professional environment, regardless of the job.
• Time management – The ability to prioritise and organise tasks is a tremendous asset in the professional industry. A PhD holder can use their qualification to demonstrate that they are able to manage their time, arrange and follow a plan, and stick to deadlines.
• Report writing – Condensing three years of work into a thesis demonstrates your ability to filter through massive amounts of information, identify the key points, and get these points across to the reader. The ability to ‘cut out the waffle’ or ‘get to the point’ is a huge asset in the professional industry.

Aside from the above, you also get to refer to yourself as a Doctor and add fancy initials after your name!

What Can I Do After a PhD?

One of the most desirable postdoctoral fields is working within independent Research and Development (R&D) labs and new emerging companies. Both industries, especially R&D labs, have dedicated groups of PhD graduates who lead research activities, design new products and take part in crucial strategic meetings. Not only is this a stimulating line of work, but the average salaries in R&D labs and emerging start-ups are lucrative. In comparison, an undergraduate with five years of experience within their given field will, on average, likely earn less than a new PhD graduate taking on a R&D position.

It’s a common misunderstanding that PhDs only opens the door for an academic career such as university lecturers and training providers. Although obtaining a PhD opens these doors, the opportunities extend far beyond educational roles. In fact, recent data from the UK’s Higher Education Statistics Agency (HESA) indicates only 23% of PhD graduates take a position in educational roles . This low percentage is primarily because PhD graduates have a wide range of skills that make them suitable for a broad spectrum of roles. This is being seen first hand by the increasing number of PhD graduates who are entering alternative roles such as research, writing, law and investment banking.

How Do I Find a PhD?

We appreciate that finding a PhD programme to undertake can be a relatively daunting process. According to Higher Education Student Statistics , over 22,000 PhDs were awarded in 2016/17 within the United Kingdom alone. Clearly there are a huge number of PhD programmes available. This can sometimes be confusing for prospective doctorates, particularly when different programmes are advertised in different places. Often, it is difficult to know where to look or where to even start. We’ve put together a list of useful sources to find the latest PhD programmes:

• A great place to start is with our comprehensive and up-to-date database of available PhD positions .
• Assuming you are still at university, speak to an existing PhD supervisor within your department.
• Attend as many postgraduate open days as you can. Whilst there, speak to current PhD students and career advisors to get an awareness of what PhDs are on offer.
• Visit the postgraduate section of university websites and the PhD Research Council section of the UKRI website.

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PhD Student Tips How to Write Dissertation Aims and Objectives

PhD students, get your dissertation off to a great start with my tips for aims and objectives!

Let's dive into the often misunderstood territory of aims and objectives – those crucial elements that form the foundation of your thesis.

Understanding the Basics: Aims vs. Objectives

First things first, let's clear the air about aims and objectives. Aims are your research's North Star, the big picture outcomes you're striving for. They're about the impact, the change your project will usher in.

Objectives, on the other hand, are the nitty-gritty tasks you must tackle to reach those lofty aims.

In my two decades of guiding master's and PhD students, I've seen many stumble over aims and objectives like an academic obstacle course. But fear not – I'm here to set the record straight and share some hacks to ensure you crush those aims and objectives with confidence.

The Aims: Painting the Big Picture

Your aims should be clear, focused, and limited to three, forcing you to zero in on what truly matters. Here are some examples you might want to borrow!

To advance the understanding of…

To create a novel framework for…

To enhance the effectiveness of…

To establish a comprehensive…

To investigate the impact of…

To develop a model for…

To foster knowledge-sharing among…

To transform current perceptions of…

To generate a comprehensive set of…

Feel free to screenshot these for your reference!

The Objectives: Nuts and Bolts of Your Research Strategy

Now, let's talk objectives. These are the actionable steps you take to achieve your aims.

Use dynamic words like calculate, clarify, define, locate, explain, formulate, identify , and the list goes on.

But, there's a catch – don't turn your objectives into a mundane list of dissertation chapters. Your objectives should be sophisticated, spanning across multiple chapters and showing a logical progression, which is where the cake comes in. Bear with me, it will all make sense soon!

Building the Objective Sponge Cake: Layering Matters

Think of your objectives like a sponge cake with three layers. The first sponge layer comprises simpler, foundational objectives. The middle jammy layer delves into rich, in-depth activities. The top sponge layer ties it all together, asking the crucial "So what?" questions. Here's a taste from a made up research project!

Understanding Climate Change Impacts on Coastal Ecosystems

Sponge: Clarify the key indicators of climate change impacts on coastal ecosystems.

Jam: Analyze historical data to identify trends in temperature, sea level, and biodiversity changes.

Sponge: Recommend adaptive strategies for coastal communities based on the analysis of climate change impacts.

The Devil's in the Details: Be Specific

When crafting objectives, specificity is your ally.

Avoid vague terms like "do," "study," "look at," or "learn about."

Instead, ask yourself, "What does doing actually involve?" and "What do I mean by study?" Being specific ensures your objectives are laser-focused and leaves no room for ambiguity.

And there you have it – a crash course in aims and objectives tailored just for you. Before you go, don't forget to grab the cheat sheet by clicking the button below. It condenses the key points from this blog and arms you with a treasure trove of words for your aims and objectives.

Come back soon for more tips on all things PhD. Until then, happy researching!

What’s the difference between qualitative and quantitative research interviews?

How to do ethnography: top tips for graduate school phd students.

PhD Thesis Guide

This phd thesis guide will guide you step-by-step through the thesis process, from your initial letter of intent to submission of the final document..

All associated forms are conveniently consolidated in the section at the end.

Deadlines & Requirements

Students should register for HST.ThG during any term in which they are conducting research towards their thesis. Regardless of year in program students registered for HST.ThG in a regular term (fall or spring) must meet with their research advisor and complete the  Semi-Annual PhD Student Progress Review Form to receive credit.

Years 1 - 2

• Students participating in lab rotations during year 1, may use the optional MEMP Rotation Registration Form , to formalize the arrangement and can earn academic credit by enrolling in HST.599. 
• A first letter of intent ( LOI-1 ) proposing a general area of thesis research and research advisor is required by April 30th of the second year of registration.
• A second letter of intent ( LOI-2 ) proposing a thesis committee membership and providing a more detailed description of the thesis research is required by April 30th of the third year of registration for approval by the HST-IMES Committee on Academic Programs (HICAP).

Year 4 

• Beginning in year 4, (or after the LOI-2 is approved) the student must meet with their thesis committee at least once per semester.
• Students must formally defend their proposal before the approved thesis committee, and submit their committee approved proposal to HICAP  by April 30 of the forth year of registration.
• Meetings with the thesis committee must be held at least once per semester. 

HST has developed these policies to help keep students on track as they progress through their PhD program. Experience shows that students make more rapid progress towards graduation when they interact regularly with a faculty committee and complete their thesis proposal by the deadline.

Getting Started

Check out these resources  for finding a research lab.

The Thesis Committee: Roles and Responsibilities

Students perform doctoral thesis work under the guidance of a thesis committee consisting of at least three faculty members from Harvard and MIT (including a chair and a research advisor) who will help guide the research. Students are encouraged to form their thesis committee early in the course of the research and in any case by the end of the third year of registration. The HST IMES Committee on Academic Programs (HICAP) approves the composition of the thesis committee via the letter of intent and the thesis proposal (described below). 

Research Advisor

The research advisor is responsible for overseeing the student's thesis project. The research advisor is expected to:

• oversee the research and mentor the student;
• provide a supportive research environment, facilities, and financial support;
• discuss expectations, progress, and milestones with the student and complete the  Semi-Annual PhD Student Progress Review Form each semester;
• assist the student to prepare for the oral qualifying exam;
• guide the student in selecting the other members of the thesis committee;
• help the student prepare for, and attend, meetings of the full thesis committee, to be held at least once per semester;
• help the student prepare for, and attend, the thesis defense;
• evaluate the final thesis document.

The research advisor is chosen by the student and must be a faculty member of MIT* or Harvard University and needs no further approval.  HICAP may approve other individuals as research advisor on a student-by-student basis. Students are advised to request approval of non-faculty research advisors as soon as possible.  In order to avoid conflicts of interest, the research advisor may not also be the student's academic advisor. In the event that an academic advisor becomes the research advisor, a new academic advisor will be assigned.

The student and their research advisor must complete the Semi-Annual PhD Student Progress Review during each regular term in order to receive academic credit for research.  Download Semi Annual Review Form

*MIT Senior Research Staff are considered equivalent to faculty members for the purposes of research advising. No additional approval is required.

Thesis Committee Chair

Each HST PhD thesis committee is headed administratively by a chair, chosen by the student in consultation with the research advisor. The thesis committee chair is expected to:

• provide advice and guidance concerning the thesis research; 
• oversee meetings of the full thesis committee, to be held at least once per semester;
• preside at the thesis defense; 
• review and evaluate the final thesis document.

The thesis committee chair must be well acquainted with the academic policies and procedures of the institution granting the student's degree and be familiar with the student's area of research. The research advisor may not simultaneously serve as thesis committee chair.

For HST PhD students earning degrees through MIT, the thesis committee chair must be an MIT faculty member. A select group of HST program faculty without primary appointments at MIT have been pre-approved by HICAP to chair PhD theses awarded by HST at MIT in cases where the MIT research advisor is an MIT faculty member.**

HST PhD students earning their degree through Harvard follow thesis committee requirements set by the unit granting their degree - either the Biophysics Program or the School of Engineering and Applied Sciences (SEAS).

** List of non-MIT HST faculty approved to chair MIT thesis proposals when the research advisor is an MIT faculty member.

In addition to the research advisor and the thesis committee chair, the thesis committee must include one or more readers. Readers are expected to:

• attend meetings of the full thesis committee, to be held at least once per semester;
• attend the thesis defense; 

Faculty members with relevant expertise from outside of Harvard/MIT may serve as readers, but they may only be counted toward the required three if approved by HICAP.

The members of the thesis committee should have complementary expertise that collectively covers the areas needed to advise a student's thesis research. The committee should also be diverse, so that members are able to offer different perspectives on the student's research. When forming a thesis committee, it is helpful to consider the following questions: 

• Do the individuals on the committee collectively have the appropriate expertise for the project?
• Does the committee include at least one individual who can offer different perspectives on the student's research?  The committee should include at least one person who is not closely affiliated with the student's primary lab. Frequent collaborators are acceptable in this capacity if their work exhibits intellectual independence from the research advisor.
• If the research has a near-term clinical application, does the committee include someone who can add a translational or clinical perspective?  
• Does the committee conform to HST policies in terms of number, academic appointments, and affiliations of the committee members, research advisor, and thesis committee chair as described elsewhere on this page?

[Friendly advice: Although there is no maximum committee size, three or four is considered optimal. Committees of five members are possible, but more than five is unwieldy.]

Thesis Committee Meetings

Students must meet with their thesis committee at least once each semester beginning in the fourth year of registration. It is the student's responsibility to schedule these meetings; students who encounter difficulties in arranging regular committee meetings can contact Julie Greenberg at jgreenbe [at] mit.edu (jgreenbe[at]mit[dot]edu) .

The format of the thesis committee meeting is at the discretion of the thesis committee chair. In some cases, the following sequence may be helpful:

• The thesis committee chair, research advisor, and readers meet briefly without the student in the room;
• The thesis committee chair and readers meet briefly with the student, without the advisor in the room;
• The student presents their research progress, answers questions, and seeks guidance from the members of the thesis committee;

Please note that thesis committee meetings provide an important opportunity for students to present their research and respond to questions. Therefore, it is in the student's best interest for the research advisor to refrain from defending the research in this setting.

Letters of Intent

Students must submit two letters of intent ( LOI-1 and LOI-2 ) with applicable signatures. 

In LOI-1, students identify a research advisor and a general area of thesis research, described in 100 words or less. It should include the area of expertise of the research advisor and indicate whether IRB approval (Institutional Review Board; for research involving human subjects) and/or IACUC approval (Institutional Animal Care and Use Committee; for research involving vertebrate animals) will be required and, if so, from which institutions. LOI-1 is due by April 30 of the second year of registration and and should be submitted to HICAP, c/o Traci Anderson in E25-518. 

In LOI-2, students provide a description of the thesis research, describing the Background and Significance of the research and making a preliminary statement of Specific Aims (up to 400 words total). In LOI-2, a student also proposes the membership of their thesis committee. In addition to the research advisor, the proposed thesis committee must include a chair and one or more readers, all selected to meet the specified criteria . LOI-2 is due by April 30th of the third year of registration and should be submitted to HICAP, c/o Traci Anderson in E25-518.

LOI-2 is reviewed by the HST-IMES Committee on Academic Programs (HICAP) to determine if the proposed committee meets the specified criteria and if the committee members collectively have the complementary expertise needed to advise the student in executing the proposed research. If HICAP requests any changes to the proposed committee, the student must submit a revised LOI-2 for HICAP review by September 30th of the fourth year of registration. HICAP must approve LOI-2 before the student can proceed to presenting and submitting their thesis proposal. Any changes to the thesis committee membership following HICAP approval of LOI-2 and prior to defense of the thesis proposal must be reported by submitting a revised LOI-2 form to HICAP, c/o tanderso [at] mit.edu (Traci Anderson) . After final HICAP approval of LOI-2, which confirms the thesis committee membership, the student may proceed to present their thesis proposal to the approved thesis committee, as described in the next section.

Students are strongly encouraged to identify tentative thesis committee members and begin meeting with them as early as possible to inform the direction of their research. Following submission of LOI-2, students are required to hold at least one thesis committee meeting per semester. Students must document these meetings via the Semi- Annual PhD Student Progress Review form in order to receive a grade reflecting satisfactory progress in HST.ThG.

Thesis Proposal and Proposal Presentation

For MEMP students receiving their degrees through MIT, successful completion of the Oral Qualifying Exam is a prerequisite for the thesis proposal presentation. For MEMP students receiving their degrees through Harvard, the oral qualifying exam satisfies the proposal presentation requirement.

Proposal Document

Each student must present a thesis proposal to a thesis committee that has been approved by HICAP via the LOI-2 and then submit a full proposal package to HICAP by April 30th of the fourth year of registration. The only exception is for students who substantially change their research focus after the fall term of their third year; in those cases the thesis proposal must be submitted within three semesters of joining a new lab. Students registering for thesis research (HST.THG) who have not met this deadline may be administratively assigned a grade of "U" (unsatisfactory) and receive an academic warning.

The written proposal should be no longer than 4500 words, excluding references. This is intended to help students develop their proposal-writing skills by gaining experience composing a practical proposal; the length is comparable to that required for proposals to the NIH R03 Small Research Grant Program. The proposal should clearly define the research problem, describe the proposed research plan, and defend the significance of the work. Preliminary results are not required. If the proposal consists of multiple aims, with the accomplishment of later aims based on the success of earlier ones, then the proposal should describe a contingency plan in case the early results are not as expected.

Proposal Presentation

The student must formally defend the thesis proposal before the full thesis committee that has been approved by HICAP.

Students should schedule the meeting and reserve a conference room and any audio visual equipment they may require for their presentation. To book a conference room in E25, please contact Joseph Stein ( jrstein [at] mit.edu (jrstein[at]mit[dot]edu) ).

Following the proposal presentation, students should make any requested modifications to the proposal for the committee members to review. Once the committee approves the proposal, the student should obtain the signatures of the committee members on the forms described below as part of the proposal submission package.

[Friendly advice: As a professional courtesy, be sure your committee members have a complete version of your thesis proposal at least one week in advance of the proposal presentation.]

Submission of Proposal Package

When the thesis committee has approved the proposal, the student submits the proposal package to HICAP, c/o Traci Anderson in E25-518, for final approval. HICAP may reject a thesis proposal if it has been defended before a committee that was not previously approved via the LOI-2.

The proposal package includes the following: 

• the proposal document
• a brief description of the project background and significance that explains why the work is important;
• the specific aims of the proposal, including a contingency plan if needed; and
• an indication of the methods to be used to accomplish the specific aims.
• signed research advisor agreement form(s);
• signed chair agreement form (which confirms a successful proposal defense);
• signed reader agreement form(s).

Thesis Proposal Forms

• SAMPLE Title Page (doc)
• Research Advisor Agreement Form (pdf)
• Chair Agreement Form (pdf)
• Reader Agreement Form (pdf)

Thesis Defense and Final Thesis Document

When the thesis is substantially complete and fully acceptable to the thesis committee, a public thesis defense is scheduled for the student to present his/her work to the thesis committee and other members of the community. The thesis defense is the last formal examination required for receipt of a doctoral degree. To be considered "public", a defense must be announced to the community at least five working days in advance. At the defense, the thesis committee determines if the research presented is sufficient for granting a doctoral degree. Following a satisfactory thesis defense, the student submits the final thesis document, approved by the research advisor, to Traci Anderson via email (see instructions below).

[Friendly advice: Contact jrstein [at] mit.edu (Joseph Stein) at least two weeks before your scheduled date to arrange for advertising via email and posters. A defense can be canceled for insufficient public notice.]

Before the Thesis Defense 

Committee Approves Student to Defend: The thesis committee, working with the student and reviewing thesis drafts, concludes that the doctoral work is complete. The student should discuss the structure of the defense (general guidelines below) with the thesis committee chair and the research advisor. 

Schedule the Defense: The student schedules a defense at a time when all members of the thesis committee will be physical present. Any exceptions must be approved in advance by the IMES/HST Academic Office.

Reserve Room: It is the student's responsibility to reserve a room and any necessary equipment. Please contact imes-reservation [at] mit.edu (subject: E25%20Room%20Reservation) (IMES Reservation) to  reserve rooms E25-140, E25-141, E25-119/121, E25-521. 

Final Draft: A complete draft of the thesis document is due to the thesis committee two weeks prior to the thesis defense to allow time for review.  The thesis should be written as a single cohesive document; it may include content from published papers (see libraries website on " Use of Previously Published Material in a Thesis ") but it may not be a simple compilation of previously published materials.

Publicize the Defense:   The IMES/HST Academic Office invites the community to attend the defense via email and a notice on the HST website. This requires that the student email a thesis abstract and supplemental information to  jrstein [at] mit.edu (Joseph Stein)  two weeks prior to the thesis defense. The following information should be included: Date and time, Location, (Zoom invitation with password, if offering a hybrid option), Thesis Title, Names of committee members, with academic and professional titles and institutional affiliations. The abstract is limited to 250 words for the poster, but students may optionally submit a second, longer abstract for the email announcement.

Thesis Defense Guidelines

Public Defense: The student should prepare a presentation of 45-60 minutes in length, to be followed by a public question and answer period of 15–30 minutes at discretion of the chair.

Committee Discussion:  Immediately following the public thesis presentation, the student meets privately with the thesis committee and any other faculty members present to explore additional questions at the discretion of the faculty. Then the thesis committee meets in executive session and determines whether the thesis defense was satisfactory. The committee may suggest additions or editorial changes to the thesis document at this point.

Chair Confirms Pass: After the defense, the thesis committee chair should inform Traci Anderson of the outcome via email to tanderso [at] mit.edu (tanderso[at]mit[dot]edu) .

Submitting the Final Thesis Document

Please refer to the MIT libraries  thesis formatting guidelines .

Title page notes. Sample title page  from the MIT Libraries.

Program line : should read, "Submitted to the Harvard-MIT Program in Health Sciences and Technology, in partial fulfillment of the the requirements for the degree of ... "

Copyright : Starting with the June 2023 degree period and as reflected in the  MIT Thesis Specifications , all students retain the copyright of their thesis.  Please review this section for how to list on your title page Signature Page: On the "signed" version, only the student and research advisor should sign. Thesis committee members are not required to sign. On the " Accepted by " line, please list: Collin M. Stultz, MD, PhD/Director, Harvard-MIT Program in Health Sciences and Technology/ Nina T. and Robert H. Rubin Professor in Medical Engineering and Science/Professor of Electrical Engineering and Computer Science.

The Academic Office will obtain Professor Stultz's signature.

Thesis Submission Components.  As of 4/2021, the MIT libraries have changed their thesis submissions guidelines and are no longer accepting hard copy theses submissions. For most recent guidance from the libraries:  https://libguides.mit.edu/mit-thesis-faq/instructions  

Submit to the Academic Office, via email ( tanderso [at] mit.edu (tanderso[at]mit[dot]edu) )

pdf/A-1 of the final thesis should include an UNSIGNED title page

A separate file with a SIGNED title page by the student and advisor, the Academic Office will get Dr. Collin Stultz's signature.

For the MIT Library thesis processing, fill out the "Thesis Information" here:  https://thesis-submit.mit.edu/

File Naming Information:  https://libguides.mit.edu/

Survey of Earned Doctorates.  The University Provost’s Office will contact all doctoral candidates via email with instructions for completing this survey.

Links to All Forms in This Guide

• MEMP Rotation Form (optional)
• Semi-Annual Progress Review Form
• Letter of Intent One
• Letter of Intent Two

Final Thesis

• HST Sample thesis title page  (signed and unsigned)
• Sample thesis title page  (MIT Libraries)

Research Voyage

Research Tips and Infromation

How to Write Aims and Objectives for your Dissertation or Thesis?

Introduction

Understanding aims and objectives, crafting aims, break it down into objectives, developing specific objectives, align with research questions, consider feasibility, review and refine, seek feedback, documenting aims and objectives.

In a PhD or Post Graduate dissertation, the aims and objectives play a crucial role in shaping the research process and ensuring focus. They provide a clear roadmap for your study and serve as the guiding principles that steer your research in the right direction.

Aims represent the broader purpose or the overarching goal of your research. They define what you want to achieve with your dissertation. For example, let’s say you’re conducting a study on renewable energy sources. Your aim could be to analyze the economic viability and environmental impact of solar energy adoption in residential areas.

Objectives, on the other hand, break down the aim into specific, measurable, and achievable targets that help you accomplish your research goal. They outline the specific steps or tasks you need to undertake to fulfill the aim. Continuing with the previous example, some objectives could be:

• Evaluate the current state of solar energy technologies and their efficiency.
• Assess the economic costs and benefits associated with the installation of solar panels in residential areas.
• Analyze the environmental impact of solar energy adoption in terms of carbon emissions reduction.
• Investigate the potential barriers to the widespread adoption of solar energy in residential communities.
• Develop recommendations for policymakers and stakeholders to promote the use of solar energy in residential areas.

These objectives, when combined, address different aspects related to the aim of analyzing the economic viability and environmental impact of solar energy adoption. Each objective guides a specific aspect of the research and contributes to answering the research questions.

By having clear aims and objectives, you establish a solid framework for your study. They help you stay focused on the main purpose of your research and prevent you from getting sidetracked or overwhelmed by tangential topics. Moreover, they provide clarity to both you and your readers, ensuring that your research remains coherent and well-structured.

In summary, clear aims and objectives are instrumental in guiding the research process of a PhD dissertation. They provide a roadmap, define the research goal, and break it down into specific targets. Through the example provided, it is evident how aims and objectives bring focus to a study on renewable energy sources and solar energy adoption in residential areas.

If you are in paucity of time, not confident of your writing skills and in a hurry to complete the writing task then you can think of hiring a research consultant that solves all your problems. Please visit my article on Hiring a Research consultant for your PhD tasks for further details.

Aims and objectives play a crucial role in guiding research projects. It’s important to define these terms and differentiate between them to ensure a clear focus in your work.

Aims represent the broader purpose or goal of your study. They define what you aim to achieve through your research project. Aims provide the overarching context and direction for your work, guiding the selection of topics, methodologies, and outcomes.

Example: Suppose you’re working on a PhD dissertation in computer science with a focus on natural language processing. Your aim could be: “To develop an efficient and accurate algorithm for sentiment analysis in social media data.”

In this example, the aim highlights the objective of creating an algorithm specifically for sentiment analysis in social media data, indicating the main objective of your research.

Objectives break down the aim into specific, measurable, and achievable targets that contribute to achieving the overall goal. They are more focused and concrete than aims, outlining the steps or tasks necessary to fulfill the aim. Objectives serve as the building blocks of your research, guiding the implementation and evaluation of your work.

Example: Continuing with the previous aim, let’s define some specific objectives:

• Collect and preprocess a large dataset of social media posts for sentiment analysis.
• Explore and compare existing sentiment analysis techniques to identify their limitations and strengths.
• Design and develop a novel algorithm that addresses the limitations of current approaches.
• Implement the algorithm and evaluate its performance on the collected dataset.
• Analyze the results and compare them with existing state-of-the-art sentiment analysis methods.

These objectives, when combined, address different aspects necessary to fulfill the aim of developing an efficient and accurate sentiment analysis algorithm for social media data. Each objective represents a specific task or milestone that contributes to the overall research goal.

The relationship between aims and objectives is critical in driving research. Objectives are derived from the aim and provide the means to accomplish it. They act as stepping stones, guiding the researcher towards achieving the broader aim.

In summary, aims provide the broader context and goal, while objectives break down the aim into specific tasks and milestones. Together, they ensure focus and direction in your research, guiding the selection of topics, methodologies, and outcomes. The objectives serve as the means to achieve the overall aim, highlighting the relationship between aims and objectives in driving research in the computer science domain.

Formulating the overarching aim of your research is a crucial step in defining the direction and purpose of your dissertation. The aim represents the primary goal or intention of your study, and crafting it effectively is essential for setting the foundation of your research.

Research Topic: Enhancing cybersecurity in cloud computing environments.

In this example, the aim focuses on improving cybersecurity in the context of cloud computing. The aim should be formulated in a concise and focused manner that aligns with the research topic. Here’s an example of how the aim could be crafted effectively:

Aim: Develop an efficient and robust security framework for ensuring data confidentiality, integrity, and availability in cloud computing environments.

The above aim encapsulates the overall goal of the research, which is to develop a security framework for enhancing cybersecurity in cloud computing. It clearly states the intention to address key aspects such as data confidentiality, integrity, and availability. The aim is concise, specific, and directly aligned with the research topic.

The significance of a well-defined aim cannot be overstated. It serves as a guiding beacon throughout your research journey, providing a clear direction and purpose. A well-crafted aim helps you stay focused and ensures that your efforts are aligned with the research’s core objectives. It also helps you communicate the purpose of your study to others, including your advisor, peers, and potential readers of your dissertation.

Additionally, an effective aim sets the stage for the subsequent development of specific objectives and research questions. It serves as a foundation upon which you can break down the aim into smaller, manageable objectives that contribute to achieving the overall research goal. Each objective should align with the aim and work together harmoniously to address the research questions and gaps in the field.

Moreover, a concise and aligned aim allows readers to quickly grasp the essence of your research. It provides them with a clear understanding of the research’s scope and purpose. By stating the aim concisely and aligning it with the research topic, you demonstrate your ability to articulate the core objective of your study in a succinct manner.

In summary, crafting effective aims involves formulating the overarching goal or intention of your research in a concise and focused manner. A well-defined aim sets the direction for your dissertation, guiding your efforts and ensuring alignment with the research topic. It serves as a foundation for the development of specific objectives and research questions. By presenting a clear and aligned aim, you convey the purpose of your study to others and demonstrate your ability to articulate the core objective of your research.

After defining the aim of your research, it’s important to break it down into smaller, manageable objectives. These objectives should address key research questions or subtopics that are necessary to achieve the overall aim. Additionally, objectives should be specific, measurable, and utilize action verbs to describe the intended actions or achievements.

Example: Suppose the aim of your research is to develop a recommendation system for an e-commerce platform. Here are some examples of specific objectives:

• Action Verbs: Analyze, Identify
• Description: Gather and analyze user preferences and historical data from the e-commerce platform to identify patterns in user behavior and item preferences.
• Action Verbs: Design, Implement
• Description: Develop and implement collaborative filtering algorithms, such as user-based or item-based methods, to generate personalized recommendations based on user similarities or item similarities.
• Action Verbs: Incorporate
• Description: Integrate machine learning techniques, such as matrix factorization or deep learning models, into the recommendation system to improve the accuracy and personalization of the recommendations.
• Action Verbs: Evaluate
• Description: Conduct experiments and evaluate the performance of the recommendation system using appropriate evaluation metrics, such as precision, recall, or mean average precision, to assess the effectiveness and efficiency of the system.
• Action Verbs: Optimize
• Description: Identify and implement optimization techniques, such as parallel computing or distributed systems, to enhance the scalability and efficiency of the recommendation algorithm, allowing it to handle large-scale datasets and real-time recommendations.

By breaking down the aim into these specific objectives, you address key components of developing a recommendation system, such as data analysis, algorithm design, evaluation, and optimization. Each objective represents a distinct step that contributes to achieving the overall aim.

Importantly, these objectives are specific and measurable, allowing you to determine whether you have successfully achieved them. For instance, you can measure the accuracy of the recommendation system, evaluate its performance against baseline models, or assess its scalability in terms of handling large datasets.

In summary, when conducting research, breaking down the aim into specific objectives helps in managing the workload and providing a clear roadmap for your research. These objectives should address key research questions or subtopics, be specific and measurable, and use action verbs to describe the intended actions or achievements. By following this approach, you can ensure a systematic and focused research process.

To develop specific objectives for your research, you need to break down the overarching aim into smaller, measurable objectives. These objectives should be clear, specific, and actionable, providing a roadmap for your research and guiding the entire research process.

Aim: Develop a machine learning-based system for automated sentiment analysis in social media data.

Objective 1: Conduct a comprehensive literature review on existing sentiment analysis techniques and methodologies.

• Breakdown: This objective focuses on reviewing the literature in the field of sentiment analysis, specifically examining the various techniques and methodologies that have been developed and applied. It involves gathering and analyzing research papers, books, and other relevant sources to gain a comprehensive understanding of the existing knowledge in sentiment analysis.

Objective 2: Collect a large dataset of social media posts for training and evaluation.

• Breakdown: This objective entails the collection of a substantial amount of social media data that will be used as input for training and evaluating the machine learning model. It involves designing data collection mechanisms, such as web scraping or utilizing available APIs, to gather a diverse set of social media posts from platforms like Twitter or Facebook.

Objective 3: Design and implement a machine learning algorithm capable of accurately detecting sentiment polarity in social media text.

• Breakdown: This objective focuses on the development of a machine learning algorithm tailored for sentiment analysis in social media text. It involves designing and implementing the necessary algorithms, selecting appropriate feature representations, and training a model to accurately classify sentiment polarity (positive, negative, or neutral) of social media posts.

Objective 4: Evaluate the performance of the developed sentiment analysis system against benchmark datasets and compare it with existing state-of-the-art approaches.

• Breakdown: This objective involves assessing the performance of the developed sentiment analysis system by evaluating it against established benchmark datasets. It requires selecting appropriate evaluation metrics and comparing the system’s performance with existing state-of-the-art approaches in sentiment analysis, such as accuracy, precision, recall, or F1 score.

The importance of clear, specific objectives cannot be overstated. These objectives provide a clear roadmap and direction for your research, guiding your efforts and ensuring that you stay on track. They help you structure your research activities, allocate resources effectively, and measure progress along the way.

Using action verbs to articulate objectives effectively is another crucial aspect. Action verbs convey specific actions or achievements that need to be accomplished. They provide clarity and precision, leaving no room for ambiguity. For example:

By using action verbs, you explicitly state what needs to be done or achieved in each objective, making it easier to track progress and assess the completion of objectives.

In summary, developing specific objectives involves breaking down the overarching aim into smaller, measurable objectives. Clear and specific objectives provide a roadmap for your research and guide the entire research process. By using action verbs, you articulate objectives effectively, leaving no room for ambiguity. These objectives help structure your research activities, allocate resources effectively, and measure progress, ultimately leading to the successful completion of your research.

When formulating objectives for your research, it is essential to ensure that they align with the research questions you have formulated. Each objective should contribute to addressing or answering a specific research question, creating a cohesive and focused research framework.

Example: Suppose your research in computer science focuses on developing an automated system for detecting and preventing cybersecurity threats. Here are examples of objectives aligned with research questions:

Research Question: How can machine learning algorithms be utilized to detect and mitigate cybersecurity threats effectively?

Objective 1: Evaluate and compare different machine learning algorithms for cybersecurity threat detection.

• Description: Explore and assess various machine learning algorithms, such as decision trees, random forests, or neural networks, to identify the most suitable approach for detecting cybersecurity threats accurately and efficiently.

Objective 2: Develop a dataset representative of diverse cybersecurity threats.

• Description: Create a comprehensive dataset containing various types of cybersecurity threats, including malware, phishing attacks, and network intrusions, to train and evaluate the machine learning models effectively.

Research Question: What are the key challenges and vulnerabilities in existing cybersecurity systems that need to be addressed?

Objective 3: Conduct a systematic analysis of existing cybersecurity systems and identify vulnerabilities.

• Description: Analyze and evaluate existing cybersecurity systems, such as intrusion detection systems or antivirus software, to identify vulnerabilities, weaknesses, and potential areas of improvement that can inform the development of a more robust automated system.

Objective 4: Propose novel techniques to enhance the resilience of the cybersecurity system.

• Description: Develop innovative approaches, such as anomaly detection algorithms or behavior-based analysis techniques, to enhance the resilience of the automated cybersecurity system and address the identified vulnerabilities.

By aligning the objectives with the research questions, you ensure that each objective contributes to addressing a specific aspect of your research. For example, Objective 1 directly addresses the research question regarding the utilization of machine learning algorithms for cybersecurity threat detection. Objective 3 focuses on analyzing existing systems to identify vulnerabilities, which is in line with the question about challenges and vulnerabilities in existing cybersecurity systems.

The alignment between research questions and objectives helps maintain a clear focus on the research objectives and ensures that your efforts are directed towards addressing the research questions. It also enhances the coherence of your research, as each objective becomes a stepping stone towards answering the research questions and achieving the overall aim of your study.

In summary, aligning objectives with research questions is crucial in research. It ensures that each objective contributes to answering or addressing a specific research question, creating a logical and cohesive framework for your study. By establishing this alignment, you can maintain a clear focus on the research objectives and make meaningful contributions to the field.

When setting objectives for your research, it is important to consider their feasibility. Feasibility refers to the realistic achievability of your objectives within the scope of your PhD research, taking into account available resources, time constraints, and other practical limitations.

Example: Suppose your research focuses on developing a new algorithm for real-time video processing and analysis. Here are examples of objectives that consider feasibility:

Objective 1: Implement the real-time video processing algorithm on a high-performance computing cluster.

• Feasibility Considerations: Before setting this objective, assess whether you have access to a high-performance computing cluster and the necessary resources (e.g., hardware, software, computational power) to support the implementation and testing of the algorithm. If such resources are available within your research environment or institution, this objective is feasible.

Objective 2: Collect and annotate a large-scale video dataset for algorithm training and evaluation.

• Feasibility Considerations: Consider the practical aspects of collecting and annotating a large-scale video dataset. Evaluate the time, manpower, and equipment required for this task. Assess whether you have access to the necessary resources (e.g., cameras, storage, annotation tools) and the capability to manage and process such a dataset. If these resources and capabilities are available within your research context, this objective is feasible.

Objective 3: Collaborate with industry partners to obtain real-world video data for testing and validation.

• Feasibility Considerations: Evaluate the feasibility of establishing collaborations with industry partners to obtain real-world video data. Consider factors such as data sharing agreements, legal and privacy considerations, and the willingness of industry partners to provide access to their data. Assess the potential challenges and limitations that may arise during this collaboration process. If such collaborations are feasible and can be established within the constraints of your research, this objective is feasible.

By considering feasibility, you ensure that your objectives are realistically achievable within the resources, time, and other constraints of your PhD research. It helps you avoid setting objectives that are too ambitious or beyond the scope of what you can reasonably accomplish.

Feasibility assessment is crucial in ensuring the successful completion of your research project. It allows you to allocate resources effectively, manage your time, and avoid potential pitfalls or setbacks that could hinder your progress. By setting feasible objectives, you can maintain a practical and manageable research plan that is more likely to lead to meaningful outcomes within the given constraints.

In summary, considering feasibility when setting objectives in computer science research is essential. Assess the available resources, time constraints, and practical limitations to ensure that your objectives are realistically achievable within the scope of your PhD research. By doing so, you can plan and execute your research effectively, making the most of the resources at your disposal and increasing the likelihood of successful outcomes.

Once you have defined your aims and objectives for your research, it’s important to review and refine them to ensure clarity, coherence, and logical flow. This step allows you to make any necessary revisions to ensure that your aims and objectives accurately reflect the scope and purpose of your research.

Example: Suppose your research in computer science focuses on developing a mobile application for enhancing cybersecurity awareness among smartphone users. Here’s an example of reviewing and refining aims and objectives:

Aim: Develop a mobile application for enhancing cybersecurity awareness among smartphone users.

Objective 1: Conduct a comprehensive literature review on cybersecurity awareness strategies and mobile application design principles.

• Review and Refinement: Upon review, you find that the objective is clear and aligned with the aim. However, you decide to refine it to include specific aspects you intend to cover in the literature review, such as user education techniques, persuasive design elements, and existing cybersecurity awareness mobile applications.

Objective 2: Design and develop a user-friendly mobile application prototype that delivers educational content and interactive features.

• Review and Refinement: During the review, you realize that the objective lacks specificity regarding the educational content and interactive features. You refine it to explicitly mention the inclusion of topics like phishing prevention, password management, and interactive quizzes to reinforce learning.

Objective 3: Conduct usability testing and collect feedback from potential users to evaluate the effectiveness of the mobile application.

• Review and Refinement: While reviewing, you realize that the objective could benefit from additional information. You refine it to include details such as the target user group (e.g., smartphone users aged 18-35), the number of participants you plan to involve in the usability testing, and the specific metrics you will use to evaluate the effectiveness of the application.

By reviewing and refining your aims and objectives, you ensure that they accurately capture the scope and purpose of your research. It helps you identify any gaps, ambiguities, or areas that need further clarification. Through this process, you can enhance the clarity, coherence, and logical flow of your aims and objectives, making them more robust and aligned with your research goals.

Additionally, reviewing and refining your aims and objectives allows you to align them with the current state of knowledge in the field. As you conduct literature reviews and gain more insights into existing research, you may discover the need to make adjustments to your aims and objectives to reflect the most relevant and up-to-date information.

In summary, reviewing and refining aims and objectives in research is essential to ensure clarity, coherence, and logical flow. By carefully reviewing each aim and objective, you can identify areas for improvement, refine them to include specific details, and align them with the current state of knowledge in the field. This process enhances the accuracy and effectiveness of your aims and objectives, providing a strong foundation for your research.

Once you have developed your aims and objectives for your research, it is important to seek feedback from your supervisor or peers. Sharing your aims and objectives with others allows you to gather valuable insights, suggestions, and perspectives that can help refine and improve your objectives, ensuring they are appropriate and aligned with your research.

Imagine you have formulated the following objectives for your computer science research on developing an intelligent tutoring system:

Objective 1: Conduct a literature review on existing intelligent tutoring systems and their effectiveness in enhancing student learning outcomes.

Objective 2: Design and develop an adaptive learning algorithm to personalize the tutoring experience based on individual student needs.

Objective 3: Implement a user-friendly interface for the intelligent tutoring system that provides an intuitive and engaging learning environment.

Objective 4: Evaluate the effectiveness of the developed intelligent tutoring system through a series of user studies and compare it with traditional tutoring methods.

At this stage, it would be beneficial to share your aims and objectives with your supervisor or peers to receive feedback. They can provide valuable insights and suggestions to help you refine and improve your objectives. For example:

• Your supervisor may suggest including a specific research question to further clarify the focus of Objective 1, such as “What are the key features and techniques used in successful intelligent tutoring systems?”
• Peers may provide feedback on the clarity and specificity of Objective 2, suggesting adding details on the specific adaptability mechanisms to be incorporated.
• Your supervisor might suggest considering the inclusion of usability testing as part of Objective 3 to ensure the interface meets the needs and preferences of the target users.
• Peers may offer suggestions on additional evaluation metrics or experimental setups to strengthen Objective 4 and provide more robust comparisons.

By seeking feedback, you open yourself up to constructive criticism and valuable perspectives that can help enhance the quality and effectiveness of your aims and objectives. Feedback from experienced researchers or knowledgeable peers can help you identify any potential gaps or weaknesses in your objectives and provide suggestions for improvement.

Remember that feedback is an iterative process, and it is important to carefully consider the suggestions provided while also critically evaluating them in the context of your research. Incorporating constructive feedback will help you refine your aims and objectives, ensuring they are robust, relevant, and aligned with your research goals.

In summary, seeking feedback on your aims and objectives is a valuable step in the process of developing your research. Sharing your objectives with your supervisor or peers allows you to gather insights, suggestions, and perspectives that can help refine and improve your objectives. Feedback helps ensure that your objectives are appropriate, clear, and aligned with your research goals, ultimately strengthening the overall quality of your research.

When writing your dissertation, it is crucial to properly document and present your aims and objectives. The placement and presentation of aims and objectives play a significant role in providing readers with a clear understanding of the research’s purpose and direction.

Placement: The aims and objectives of your research should be presented early on in your dissertation, typically within the introduction chapter. This allows readers to grasp the overall scope and intent of your research from the beginning. Placing them in the introduction helps set the context and provides a roadmap for the rest of the dissertation.

Presentation: When presenting aims and objectives, it is important to clearly distinguish between the two and articulate their role in driving the research. Here’s an example of how you can document aims and objectives:

Aims: Start by presenting the overarching aim of your research, which represents the primary goal or intention of your study. It should be a concise statement that captures the essence of your research focus.

For example:

Aim: The aim of this research is to develop a machine learning-based system for automated sentiment analysis in social media data.

Objectives: Following the aim, present a list of specific objectives that outline the key steps or milestones required to achieve the aim. Each objective should be clear, specific, and measurable. Here’s an example:

Objectives:

• Analyze existing sentiment analysis techniques and methodologies in the literature to identify their limitations and challenges.
• Collect and preprocess a large dataset of social media posts to serve as the training and evaluation data for the sentiment analysis system.
• Design and implement a machine learning algorithm capable of accurately detecting sentiment polarity in social media text.
• Evaluate the performance of the developed sentiment analysis system against existing state-of-the-art approaches, using appropriate evaluation metrics.
• Optimize the system for scalability and efficiency, allowing it to handle large volumes of real-time social media data.

By clearly documenting the aims and objectives in your dissertation, you provide readers with a clear understanding of the purpose and direction of your research. This enables them to follow your thought process and evaluate the relevance and significance of your study. Aims and objectives serve as guideposts that help readers navigate through your dissertation and understand the specific research questions you seek to address.

Moreover, the well-documented aims and objectives help you maintain focus throughout your research journey and provide a framework for organizing your dissertation. They establish the foundation upon which your methodology, analysis, and conclusions are built.

In summary, when documenting aims and objectives in a dissertation, it is important to place them in the introduction chapter and clearly present their role in guiding the research. Aims and objectives should be distinct, with the aim of capturing the overarching goal and the objectives outlining the specific steps or milestones to achieve it. By effectively documenting aims and objectives, you provide readers with a clear understanding of the research’s purpose and direction, facilitating their engagement with your work.

Crafting clear and well-defined aims and objectives is a critical aspect of writing a PhD or Post Graduate dissertation. These aims and objectives provide a solid foundation for your research, guiding your efforts and ensuring a focused and coherent study. Through this discussion, we have explored the importance of aims and objectives in a PhD dissertation and how they contribute to the research process.

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How to Write the Dissertation Aims and Objectives – Guide & Examples

Published by Grace Graffin at January 27th, 2023 , Revised On October 9, 2023

Aims and objectives are among the essential aspects of a dissertation. If you write aims and objectives effectively, they can act as a foundation to give your research clarity and focus.

This article will provide you with all the necessary information regarding aims and objectives, their differences, writing tips , and the common mistakes you should avoid while writing them.

The aim is often a single sentence or a short paragraph that describes your dissertation’s main goal and intent. It tells what you hope to achieve at the end. You should write the aim so that it becomes identifiable when it is achieved with the completion of your dissertation .

The aim is written in a subsection of the introduction to clarify the overall purpose of the dissertation .

Example: It is often observed that employees in culturally diverse workplaces struggle to work effectively in a team. A probable cause of this issue is bullying at the workplace. This research investigates the impact of bullying on employee job satisfaction at culturally diverse workplaces and the resulting loss of employee productivity. This research will use surveys and case study analysis to analyze the impact of bullying on employees.

The objectives in a dissertation describe the ways through which you intend to achieve the research aim. They are specific statements that break down the aim into several smaller key sections of the overall research. Suitable objectives can help you stay focused and conduct research in the direction of your aim.

The number of objectives should be realistic; usually, between three to six, and each one should be possible to achieve. The following example shows the objectives for the previously-mentioned dissertation aim.

1. identification of the behaviors that are considered as bullying 2. exploring the factors that cause bullying at a culturally diverse workplace 3. analyzing the relationship between bullying and job satisfaction of employees 4. providing suitable recommendations on minimizing the bullying at the workplace

The objectives of a dissertation should be SMART.

• Specific: should be precise, focused, and well-defined
• Measurable: the progress should be measurable, and you should be able to determine when you have achieved an objective.
• Achievable: you should be able to carry out the required action within your available resources
• Relevant: should be related to the dissertation aim
• Time-bound: should be possible within the available time

Differences between aims and objectives

Aims and objectives are often mixed, but there are clear differences between them.

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How to write aims and objectives?

There is no particular way or standard to write the aims and objectives. Different researchers have different writing styles, and often it can be influenced by your research supervisor. However, you should follow certain basic principles while writing aims and objectives in a dissertation.

Writing the aim statement

The aim statement should cover the following essential elements.

• Why is the research necessary? (covers the underlying problem on which the study is to be conducted)
• What is the research about? (description of the research title)
• How are you going to conduct it? (a brief statement of intended research methods)

An appropriate aim clearly defines the research purpose without confusing the reader. If you struggle to explain your research and its importance in simpler terms, you should consider refining your research to clarify it further.

Writing objectives

The objectives describe how you would achieve your research aim. You can do this through the following steps,

• The first one to two objectives can be applied to the literature review . (Verbs to be used: investigate, examine, study)
• One objective can be applied to the methodology portion. (Verbs to be used: collect, select, demonstrate, estimate)
• Two to three objectives can cover the critical evaluation or discussion chapters (Verbs to be used: analyze, compare, evaluate)
• The final objective will cover the conclusion or recommendation portion. (Verbs to be used: conclude, recommend)

Instead of writing like a paragraph, the objectives should be written as a numbered list to give them more clarity.

How many aims and objectives should be there?

It depends upon the topic of your research and mainly upon your supervisor’s requirements. Generally, a dissertation has a single broad statement as the research aim. However, it is acceptable to include a main aim along with two to three subsidiary aims.

Similarly, the number of objectives should be realistic and sufficient to measure the progress regarding the achievement of the research aim. Their number can generally vary from three to six depending upon the aim.

Common mistakes to avoid while writing research aims and objectives

• Writing a broad research aim

Writing a broad research aim is a common mistake, and it often becomes difficult to achieve. It may create a problem when you are asked to prove how you have achieved your aims during your  viva defense . It would be best to narrow your study to a specific area in the early stages of the dissertation.

• Formulating overlapping research objectives

The objectives should be written such that they are measurable and distinct from each other. If they overlap, it makes it difficult to structure your dissertation properly in specific chapters.

• Setting unrealistic aims

Students often get over-ambitious while describing the research aim and face problems afterward in achieving those aims. You should avoid this mistake and be realistic about what you can achieve in the available time and resources.

Aims and objectives are the sections that require significant time and attention to avoid future hassles while conducting research and writing your dissertation.

Frequently Asked Questions

How to set dissertation aims and objectives.

To set dissertation aims and objectives, define your research goals clearly. Aims state what you want to achieve, while objectives outline specific, measurable steps to reach those goals. Ensure they align with your research question and contribute to your study’s significance.

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Formulating Research Aims and Objectives

Formulating research aim and objectives in an appropriate manner is one of the most important aspects of your thesis. This is because research aim and objectives determine the scope, depth and the overall direction of the research. Research question is the central question of the study that has to be answered on the basis of research findings.

Research aim emphasizes what needs to be achieved within the scope of the research, by the end of the research process. Achievement of research aim provides answer to the research question.

Research objectives divide research aim into several parts and address each part separately. Research aim specifies WHAT needs to be studied and research objectives comprise a number of steps that address HOW research aim will be achieved.

As a rule of dumb, there would be one research aim and several research objectives. Achievement of each research objective will lead to the achievement of the research aim.

Consider the following as an example:

Research title: Effects of organizational culture on business profitability: a case study of Virgin Atlantic

Research aim: To assess the effects of Virgin Atlantic organizational culture on business profitability

Following research objectives would facilitate the achievement of this aim:

• Analyzing the nature of organizational culture at Virgin Atlantic by September 1, 2022
• Identifying factors impacting Virgin Atlantic organizational culture by September 16, 2022
• Analyzing impacts of Virgin Atlantic organizational culture on employee performances by September 30, 2022
• Providing recommendations to Virgin Atlantic strategic level management in terms of increasing the level of effectiveness of organizational culture by October 5, 2022

Figure below illustrates additional examples in formulating research aims and objectives:

Formulation of research question, aim and objectives

Common mistakes in the formulation of research aim relate to the following:

1. Choosing the topic too broadly . This is the most common mistake. For example, a research title of “an analysis of leadership practices” can be classified as too broad because the title fails to answer the following questions:

a) Which aspects of leadership practices? Leadership has many aspects such as employee motivation, ethical behaviour, strategic planning, change management etc. An attempt to cover all of these aspects of organizational leadership within a single research will result in an unfocused and poor work.

b) An analysis of leadership practices in which country? Leadership practices tend to be different in various countries due to cross-cultural differences, legislations and a range of other region-specific factors. Therefore, a study of leadership practices needs to be country-specific.

c) Analysis of leadership practices in which company or industry? Similar to the point above, analysis of leadership practices needs to take into account industry-specific and/or company-specific differences, and there is no way to conduct a leadership research that relates to all industries and organizations in an equal manner.

Accordingly, as an example “a study into the impacts of ethical behaviour of a leader on the level of employee motivation in US healthcare sector” would be a more appropriate title than simply “An analysis of leadership practices”.

2. Setting an unrealistic aim . Formulation of a research aim that involves in-depth interviews with Apple strategic level management by an undergraduate level student can be specified as a bit over-ambitious. This is because securing an interview with Apple CEO Tim Cook or members of Apple Board of Directors might not be easy. This is an extreme example of course, but you got the idea. Instead, you may aim to interview the manager of your local Apple store and adopt a more feasible strategy to get your dissertation completed.

3. Choosing research methods incompatible with the timeframe available . Conducting interviews with 20 sample group members and collecting primary data through 2 focus groups when only three months left until submission of your dissertation can be very difficult, if not impossible. Accordingly, timeframe available need to be taken into account when formulating research aims and objectives and selecting research methods.

Moreover, research objectives need to be formulated according to SMART principle,

 where the abbreviation stands for specific, measurable, achievable, realistic, and time-bound.

Examples of SMART research objectives

At the conclusion part of your research project you will need to reflect on the level of achievement of research aims and objectives. In case your research aims and objectives are not fully achieved by the end of the study, you will need to discuss the reasons. These may include initial inappropriate formulation of research aims and objectives, effects of other variables that were not considered at the beginning of the research or changes in some circumstances during the research process.

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PhD - Doctoral Programmes

Affiliation & Recognition

Affiliated to University of Mysore

Accreditations

NAAC ‘A’ Grade (3.25 on a scale of 4)

3 years (minimum)

Introduction

AIMS Centre for Advanced Research Centre (ACARC) is a recognized research centre of University of Mysore (UoM). This centre offers Ph.D programmes in the fields of Management, Commerce and Computer Science.

Ph.D Programme at AIMS Institutes adheres to and expects high quality standards. In addition to the norms and procedures of UoM, the research scholars, in addition to the regular course work, are also expected to attend:

Training programs on analytical tools.

Workshops on paper writing skills.

Research oriented events to be equipped by contemporary developments.

Recognised Guides and Vacancies

Dr. Kiran Reddy

Category Vacancy Availability

General Merit 1

Other Backward Classes 1

Scheduled Castes / Tribes 0

Foreign Nationals 1

*: 1 OBC seat plus either 1 GM or 1 FN seat.

Dr. Renati Jayaprakash Reddy

General Merit 0

Other Backward Classes 0

Foreign Nationals 0

Dr. B.A.Karunakara Reddy

Computer Science

In the process of guide recognition.

Important Dates

Applications for Entrance Test shall be invited only once a year and the entrance test is conducted generally during September / October.

Eligibility

Any candidate who meets the following requirements is eligible to seek registration for a Ph.D programme :

A candidate shall have Masters Degree or any other Degree / Diploma of the University or any other Degree / Diploma of any other University / Institution recognized as equivalent thereto, with minimum of 55% marks or equivalent Cumulative Grade Point Average (CGPA) or an equivalent Grade.

However, this condition is relaxed to 50% in case of:

SC/ST/Cat-I candidates.

In service candidates with a minimum of five years of regular experience associated with teaching profession as teachers/ library professionals/ physical education instructors/ laboratory staff in educational institutions

Selection Process

Admission to Ph.D. shall be through an Entrance Test only.

Applications for Entrance Test shall be invited by the University only once a year and the entrance test is conducted generally during September / October . The Registrar (Evaluation) of University of Mysore shall invite application from the eligible candidates. The Entrance Test shall consist of one paper on the broad area of Ph.D of 100 marks with 3 hours duration. Syllabus of the paper shall be framed by the respective Boards of Studies based on UGC / CSIR National Eligibility Test (NET) pattern. The question paper shall contain 50 objective type questions of one mark each, and essay type / short answer questions for 50 marks. For candidates intending to do inter / multidisciplinary research, the Entrance Test shall be a common Entrance test in a general paper and the syllabus of the paper shall be framed by the Inter / Multidisciplinary Board of Studies. A candidate securing at least 55 marks out of 100 (50 marks out of 100 i.e 50% in case of SC/ST candidates) in the Entrance Test shall be declared as eligible to apply for admission to Ph.D.

It should be noted that successful completion of entrance test just implies the eligibility of a candidate for admission to Ph.D. degree in the University, but shall not guarantee an admission to Ph.D. degree program. The results of the Entrance Test shall be declared by the Registrar (Evaluation) who shall issue the eligibility certificate to successful candidates in the Entrance Test. The eligibility certificate shall be valid for one year from the date of the entrance test till the next entrance test is notified. The process of entrance test is applicable to all candidates who intend to pursue research leading to Ph.D. degree and it shall be conducted for all research centers coming under the University by the Department concerned.

Value Added Programmes

Training programs on latest analytical tools viz., SPSS & R

Presentations by the scholars are scheduled every month in the presence of the respective guides and senior professors which help the scholars in specifying in speeding up their research works.

Course Content

Course Structure

All provisionally registered candidates shall undergo COURSE-WORK of one semester duration of 20 weeks inclusive course-end assessment. The University shall notify the time table and details of the course work including the schedule.

The suggested course structure for Ph.D Programmes in Management, Commerce and English of UoM generally consists of:

Research Methodology.

Review of Literature and Seminars.

Submission of Annual progress reports.

Two research paper publications.

Thesis submission - After 30 months (minimum).

Syllabus for research methodology for each course is of course separate.

For deatils regarding the course structure, kindly refer to the details at - http://www.uni-mysore.ac.in/sites/default/files/content/final_ph.d_notification_edited.pdf

Awarded Scholars

Guide - Dr. Kiran Reddy

Ms. Navya Bhanu - Microfinance for Urban Poor - An Evaluation of Self Help Groups in Bangalore.

Ms. Harshitha S - Impact of Work-life Balance on Performance of Women Employees in Service Industry.

Mr. Arijit Roy - Effectiveness of Advertising in Creating Brand Equity of Product Based E-Tailers.

Ms. Maria Pramila Dsouza - Impact of Accountability of Non-Governmental Organizations (NGOs) on Social Development: A Study of Select NGO's in Karnataka.

Ms. Bhavya Bhanu - Impact of Recruitment Process Outsourcing on Employee Performance in Select Information Technology Organizations.

Mr. Somayeh Azoor - Marketing of Renewable Energy - A Study of Solar Energy Users in Mysore.

Mohammad Javad Ghalambor

Guide - Dr. Kavitha Desai

Mr. Mehrdad Nazari - Strategic Planning and Performance: A Study of Select Companies in Indian Automobile Industry.

Mr. Abdolhamid Bidokht - An Evaluation of Financial Performance of Select Private Sector Banks in India.

Ms. Jyothi M.N - Human Resource Management in Banking Industry in India - A Comparative Study of Private and Foreign Banks.

Ms. Mahalakshmi S - Internet of Things in Management of Electronic Power Distribution at BESCOM.

Mr. Debopam Chakrabarti - Supply Chain Efficiency of Different Distribution Channels for Vegetables - A Study of Select Regions in Telangana.

Guide - Dr. Somanath V.S

Mr. Pramu Kumar Raje Urs M N - A Comparative Study of Green Human Resources Management Practices in Manufacturing and Information Technology Firms in Bangalore.

Ms. Satarupa Misra - Pension Plans as an Income Security - An Assessment of Employees Perception in Select Private Sector Firms.

Mr. Nagakrishna Raje Urs - Fringe Benefits and Employees Performance - A Comparative Study of Public and Private Sector Companies.

Guide - Dr. Renati Jayaprakash Reddy

Ms. Hridhya.P.K - Financial Literacy and Personal Investment Decisions by Individual Investors of Kerala.

Ms. Anas Mohammad A'bad Alkasasbeh - Time Driven Activity Based Costing (TDABC) and Profit Maximization in Jordanian Cement Factories.

Ms. Geethanjali. G - Startups in India - A Study on Challenges and Prospects of Selected Units in Bengaluru.

Mr. Davood Rismani - Role of Intellectual Capital in Value Creation through Organizational Performance - A Comparative Study of Selected Industries in India.

Mr. Papaiah - Challenges of MSMEs in Karnataka: A Study with Reference to Peenya Industrial Area, Bengaluru.

Guide - Dr. B.A.Karunakara Reddy

Mr. Hariharan.R - A Study of price fixation Mechanism in Indian Commodity Market - A Special Reference to Selected Agricultural Commodities.

Mr. Bardees Taher Ahmed Al Okab - Sustainable Development and Eco-Tourism in Yemen - A Study on IBB Province.

Mr. Mahmoud Fawzi Z. Ismail - A Study on the Modern Management Accounting Techniques for Competitive Advantage in the Jordanian Telecommunications.

Pursuing Scholars

Ms. Hemalatha - Registered.

Ms. Padmini V - Registered.

Mr. Gourav Koundal - Registered.

Mr. Vikram M - Registered.

Mr. Bhaskar Sailesh - Provisionally Registered.

Mr. Rajashekar J - Provisionally Registered.

Guide - Dr. Saurabh Srivastava

Mr. Jagadeesh Babu M K - Thesis Submitted.

Ms. Chandrika.P - Registered.

Mr. Umashankar N R - Provisionally Registered.

Mr. Vinayaka Shantesh Angadi - Thesis Submitted.

Ms. Deepthi S J - Registered.

Ms. Anita Kurian - Registered.

Ms. Sushmitha P - Provisionally Registered.

Mr. Sreedhar B.N - Provisionally Registered.

Mr. Ranganatha R - Provisionally Registered.

Ms. Shambhavi B.R - Provisionally Registered.

Mr. Nataraja - Provisionally Registered.

Ms. Pushpa M - Provisionally Registered.

Ms. Nitu Sharma - Thesis Submitted.

Ms. Sangeetha.S - Registered.

Ms. Diana Erudiyanathan - Registered.

Mr. Virupaksha J.D - Registered.

Mr. Vedanandaprabhu P.G - Registered.

Ms. Sowmyashree A - Registered.

Ms. Tejaswini S - Registered.

Mr. Chiranth. R - Registered.

Ms. Hema N - Provisionally Registered.

Dr Geethanjali G, Research Scholar 2016-2021, AIMS Centre for Research

“I am happy and privileged to state that I have completed the Doctoral Program from AIMS Centre for Advanced Research affiliated to University of Mysore and it has contributed towards my leadership and research skills. I am thankful to my mentor and guide Dr. R Jayaprakash Reddy, who nurtured my thoughts, motivated and provided me timely guidance in successful completion of my research work. The professors at AIMS Institutes are passionate researchers, hardworking and always willing to provide help. The cross cultural interaction among scholars at the research centre also gave me friends from various parts of the world.

I am always grateful to Dr. Kiran Reddy, Principal, AIMS Institutes for providing me the opportunity to participate in the Erasmus + Exchange Program at BA School of Business and Finance University, RIGA, Latvia which enhanced my research skills and international exposure. My stay at AIMS Institutes is very memorable and I thank all the Professors and the supporting staff who contributed towards my overall development”.

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Mamodafrica Phd program

Phd program in malaria modelling, building the next generation of malaria modelers in africa for sustainable public health policies.

• Program Description
• Information For Applicants
• Topic Description

Despite the widespread efforts and notable successes in preventing and treating Malaria, sustaining reductions in Malaria disease burden remains an important global challenge. Treatment and prevention efforts such as drug treatment, vector control and bed nets are beset by challenges, including a lack of adequate surveillance data. National Malaria Control Programs (NMCPs) are continuously improving systems to gather critical data on malaria surveillance, coverage, and effectiveness of interventions. Mathematical modeling and geospatial analyses are opportunities to leverage existing and emerging data sources, extracting insight from entomological, epidemiological and intervention data to inform national and regional decision-making.  

The MaModAfrica doctoral training program established at AIMS through funding from the Bill&Melinda Gates Foundation will strengthen expertise in applied mathematical and statistical malaria modeling among African academic institutions with a particular focus on the monitoring and implementation challenges faced by NMCPs. This doctoral training program will provide emerging African scientists with the opportunity to conduct research at the forefront of disease modeling, and work towards a PhD degree within a high-quality training program based in an Africa Institution, embedded in a cooperative network of international institutions. 

This transdisciplinary program will focus on state-of-the-art modeling approaches driven by real-world questions in public health to reduce the burden of Malaria in Africa. It is built on the understanding that impactful approaches in Malaria modeling require technical expertise (e.g., mathematics, statistics, computation, and data science), the ability to formalize problems coming from experimental fields (e.g., parasitology, entomology, public health, and epidemiology) and communicate efficiently on the modeling process and the models with NMCPs. 

MaModAfrica Consortium, will offer eight fully funded PhD positions in this prestigious new doctoral program. Most of the recruited students will be based in our three focus countries (Rwanda, Benin, and Mozambique) in partnership with universities and research institutions across Africa and globally. The program aims to train future African modelers, who will have an impact across academia, industry, education, and government. 

Candidates can choose from a list of proposed research topics , and MaModAfrica Consortium will assist in building a supervision team around these topics. Alternatively, candidates can suggest their own research topics, together with a proposed supervision team. Depending on the topic, candidates will enroll in appropriate graduate programs of our partner universities. Selected students start in October 2023. 

Call For Application in different Languages

Eligibility criteria  

• Master’s degree or equivalent (completed by Sept 2023) in relevant quantitative fields (e.g., mathematics, statistics, computer science, engineering, physics, bioinformatics, econometrics, infectious disease epidemiology)
• Research potential evidenced by academic performance and involvement in relevant academic activities 
• Being an African national; citizenship or permanent residence in focus country is a plus 
• Language proficiency in the spoken language(s) of focus country/countries  
• Excellent writing and communication skills 
• Willingness and ability to travel (training courses, collaborations, conferences) 
• Female applicants are highly encouraged 

Summary  

• Length of program: 3 years 
• Fully funded (stipend, equipment, health insurance, relocation costs, conference attendance, direct cost to graduating institution such as tuition fees and registration fees) 
• International supervision teams from well-known research institutions 
• Research topics that push the boundaries of Malaria modeling  
• Application Deadline: 17th March 2023
• Program start: October 2023 

Application guidelines  

The application must be submitted via AIMS application portal provided on the website . You need to have a Email account to be able to submit your application.  

Before starting the application process, please make sure to prepare the following documents in pdf format:  

• Up-to-date resume (two pages maximum, 10MB maximum size)  
• Transcripts of academic records (Bachelor and Master’s level, all in one pdf, 10MB maximum size), 

and the following information:  

• Name, affiliation, and email addresses of two persons who can provide a letter of support if asked by MaModAfrica 
• Your motivation to pursue a Ph.D. in general? Here, you can also mention plans for your future career (1500 characters maximum) 
• Topics choice (two topics max with ranking, and/or your own topic)  
• Research directions you are most interested in and why? Justify why you are qualified to pursue research in this area. Here, you can also comment on your reason for choosing the research topic selected above (3500 characters maximum) 
• Additional funding sources (if any)  

After submission, you will receive a confirmation email of your application to your Email account. You will be able to edit your application until the deadline of the call unless you hit send. 

Contact for application details: [email protected]

Supervision  

Candidates are mentored by a supervision team of 2-4 supervisors, forming a partnership between higher education institutions in Africa and internationally. Each supervision team should consist of at least one supervisor affiliated or working closely with an NMCP, and one supervisor affiliated with the graduating institution. 

The supervision team will be formed during Phase 2 of the application process in communication with shortlisted candidates, the MaModAfrica management board, and potential supervisors. Candidates have the possibility to suggest their own supervision team. 

Research topics  

Applicants can select from a list of research topics suggested by leading researchers in their field. Each candidate can choose at most two topics and rank them by preference. Alternatively, applicants are welcome to suggest their own research topics. Shortlisted candidates will be put in touch with the supervision teams that proposed their selected topics for discussions on more concrete research ideas in Phase 2 of the application process. 

Training Components  

All candidates will be invited to participate in an intensive training school in the first year of the program, organized by MaModAfrica at AIMS-Senegal. Here, candidates will acquire skills relevant to their research and broaden their subject knowledge in applied disease modeling through a small number of intensive core courses taught by top international researchers. 

The program plans to provide continuous training opportunities virtually and/or in person. Additional training components may include (but are not limited to): 

• Guided seminars and reading groups 
• Participation in transferable skills courses (academic writing, presentations skills, research methodology course) 
• Participation in translational meetings with public health specialists (NMCP, etc.) 
• Designing and delivering a mini-course (senior PhD students) 

For any inquiries reach us on [email protected]

Applicants can select from a list of 13 research topics suggested by leading researchers in their field. Each candidate can choose at most two topics and rank them by preference. Alternatively, applicants are welcome to suggest their own research topics. Shortlisted candidates will be put in touch with the supervision teams that proposed their selected topics for discussions on more concrete research ideas in Phase 2 of the application process.

Proposed topics are listed below

• Geospatial modeling of malaria hotspots in Benin  
• Enhancing malaria control by leveraging the use of routine surveillance through data science and mathematical modelling in Rwanda 
• Age-structured malaria intervention models with applications to seasonal malaria chemoprevention in Senegal
• Mapping sub-national risk to support tailored approaches to malaria control in Mozambique and Rwanda 
• Understanding the impact of malaria interventions in northern Benin to inform future strategies in the country 
• Building predictive models of malaria vector larval habitat locations for understanding the spatial determinants of malaria transmission in Mozambique
• Mathematical modeling and control of malaria transmission dynamics: Using sterile mosquito dissemination by Wolbachia bacteria in Burkina Faso  
• Molecular surveillance of malaria coupled with mathematical modelling to assess asymptomatic infections in Kenya 
• Real-time prediction of insecticide resistance in Rwanda  
• Mechanistic and geospatial models to support genomic surveillance in elimination countries such as Senegal  
• Impact and risk of deployment of Seasonal Malaria Chemoprevention in Mozambique
• Biophysical Modelling of Malaria Parasite invasion of Red Blood Cells

Detailed topic descriptions

Topic 1 : Geospatial modeling of malaria hotspots in Benin

Malaria infections and morbidity are heterogeneously distributed across both time and space. Malaria elimination, and indeed more cost effective control, requires a more detailed description of this variation and an understanding of its drivers. The student will use mathematical models, spatial statistics and an epidemiological sampling framework to understand what drives hotspots of malaria transmission in endemic settings. 

It is expected at least two publications (one methodological and another one applied). Influence vector interventions measures through the existing mosquitos control programs in Africa.  Apply for funding in order to evaluate the benefit of control measures on the defined hotspot areas. 

This project will suit a student with a Master degree in Epidemiology, Bayesian statistics, biostatistics or ecological modelling. The student will develop a high level of skill in spatial epidemiology and computation. The successful completion of this PhD will provide the opportunity for the student to work in a wide range of academic, public and private health organizations world-wide NMCPs. 

Topic 2 : Enhancing malaria control by leveraging the use of routine surveillance through data science and mathematical modelling in Rwanda  

In Rwanda, tremendous efforts have been made over the past years and significant decreases in malaria burden have been achieved. These were due to prompt interventions such as insecticide-treated mosquito nets (ITNs), indoor residual spraying (IRS) and good case management starting from the community level. However, as malaria transmission decreases and becomes more heterogeneous, it is crucial to understand how the different interventions impact transmission and tailor them accordingly in a cost-effective way. The aim of the project is to develop a quantitative, model-based approach to support the National Malaria Control Program (NMCP) of Rwanda for deciding on malaria control strategies, addressing the following objectives: 

• Using the routine data for understanding and characterizing the epidemiological situation in Rwanda, evaluating the routine surveillance system in Rwanda 
• Estimating the impact of deployed interventions over time 
• Estimating the impact of reducing or replacing IRS with other interventions given budget constraints 
• Estimating the effect of case management and identifying its cost-effective coverage as well as supporting human resource and commodities planning 

In this PhD, the candidate will dive deep into understanding the malaria routine surveillance system in Rwanda, specifically the different data collected, consisting of various indicators about malaria burden, intervention deployment, as well as geography-specific data (e.g., seasonality). First, using various statistical methods, the candidate will analyze the historical time series and quantify the effects of deployed interventions over time. The results of this analysis will be subsequently used to parameterize an individual model of malaria transmission reproducing the malaria transmission dynamics at various administrative resolutions across the country. This model will allow analysis of several scenarios investigating the potential impact of alternative control interventions. Specifically, the PhD will entail: 

• Using statistical methods to conduct descriptive analysis of the available routine epidemiological data to understand the evolution of the local malaria situation 
• Modelling malaria transmission and the effects of malaria control interventions in Rwanda and conducting scenario analysis to predict the impact of various potential intervention strategies 
• Communicating results of analyses and supporting the NMCP 

We expect from the candidate to have the following skills and qualifications: 

• Master’s Degree in epidemiology, any other public-health-related or quantitative topic with experience in working on infectious diseases 
• Curiosity about the PhD research topic, self-initiative in communicating with the different collaborators, and more specifically with the NMCP to ensure that the conducted analyses are supporting the country needs 
• Strong quantitative background (e.g., mathematics, computer science, physics, bioinformatics) with knowledge of statistics and data analysis (e.g., time series analysis) 
• Strong coding skills, experience with R or Python 
• Being familiar with version control (e.g., git)  
• Being familiar with using Unix systems (i.e., using the Unix console and scripting language) and with running analyses in a high-performance computing environment 

Topic 3 : Age-structured malaria intervention models with applications to seasonal malaria chemoprevention in Senegal  

Malaria interventions such as seasonal malaria chemoprevention (SMC) or vaccination showed promising results from randomized control trials or pilot studies. Nevertheless, when implemented by the malaria programs at larger scale, evidence for population-level efficiency is difficult to establish owing to various sources of heterogeneity. 

In this project, the candidate will investigate heterogeneities related to age structures, which are particularly important for chemoprevention and vaccination. Using partial differential equations, we consider the age of infection (infectiousness to vectors), age of host (morbidity, mortality, immunity), age of intervention (time-dependent intervention efficacy). Concurrently with numerical simulations, the candidate will also explore physics-informed neural networks to approximate solutions in analytically intractable situations. 

In collaboration with public health specialists from Senegal, the candidate will apply the modeling framework to evaluate the impact of SMC in the past and how to best combine SMC with vaccination for future planning in terms of age targets and deployment schemes (cohort, catch-up, seasonal) at the subnational level. 

The candidate is required to have a firm quantitative undergraduate background (e.g. physics, mathematics, statistics, computer science) with basic knowledge about machine learning or dynamical systems. We require solid coding skills (e.g. C++, R, python, julia or Matlab) and familiarity with the challenges of high performance computing. Awareness for biological mechanisms and operational challenges, as well as efficient communication in a multidisciplinary environment are a plus. 

Topic 4 : Mapping sub-national risk to support tailored approaches to malaria control in Mozambique and Rwanda  

Despite significant declines in malaria burden and mortality, many endemic countries face the challenges of plateaued progress, pressures of external funding and the need to optimize limited resources in strategic and tailored approaches.  

Disease risk maps are an essential tool in the fight against malaria, supporting data-evidenced decision making by enabling better targeting of malaria interventions and can be a standardized resource to track progress and facilitate our understanding of seasonal profiles of malaria in national and sub-national levels. As countries improve their disease surveillance tools, it enables modelers to design and develop more novel statistical and mathematical approaches which incorporate multiple datasets at varied spatial and temporal scales. 

 The main goal of this research is to develop multi-metric geostatistical and mechanistic models tailored to specific operationally relevant questions prioritized by malaria endemic countries. This PhD would take the form of a) scoping a novel problem in collaboration with PNCM Mozambique and Rwanda and then b) solving that problem by developing new statistical methods building on existing work where appropriate. Relevant topics may include modelling spatio-temporal patterns of incidence and prevalence (and their relationship), urban malaria, outbreaks, malaria persistence, vector dynamic and species distribution, risk in special populations (pregnant women and infants) and malaria co-morbidity (with anemia, schistosomiasis/helminths, malnutrition). A successful candidate would be expected to spend time with the MAP team in Perth to learn advanced geostatistical techniques and will have access to MAPs comprehensive library of high-resolution environmental and demographic covariates to supplement their work. Additionally, dissemination of modelled outputs back to PNCM Mozambique and development of tools to embed into the current surveillance system is key. Successful candidate would also contribute to local capacity building to improve uptake of modelled work in decision making processes. 

Topic 5 : Understanding the impact of malaria interventions in northern Benin to inform future strategies in the country  

Despite increased funding towards the universal scale-up of malaria control prevention, mainly through insecticide-treated bed nets (ITNs), SMC and treatment with artemisinin-based combination therapy (ACT), progress has stalled in many countries in recent years. There need to be on track to achieving national and global targets for 2020 and 2025 as defined in the World Health Organization Global Technical Strategy. One of the causes is the need for more appropriate allocation of limited resources by the NMCPs from high malaria burden countries.  

To maximize progress in these countries, achieve malaria control and move toward its elimination, it is required for these countries to tailor the malaria interventions based on an adequate selection of intervention mixes for specific risk areas. This approach needs sub-national stratification of multiple malaria risk indicators from vector biology, parasite information, human behavior and routine health surveillance data, which could be combined into an overall malaria risk score per specific risk areas related to the local context in the country. This can be done with the use of mathematical modelling to predict the impact that different strategies might have. 

In Benin, from 2006 to 2010, 2011 to 2018 and from 2017 to 2021, NMCP defined several strategies related to the intensification of malaria control, which was based on the use of Long-lasting Insecticide Treated Nets (LLINs) in all the country, indoor residual spraying (IRS) in some health district, intermittent preventive treatment in pregnant women (IPTp-SP) with sulfadoxine-pyrimethamine, and treatment with artemisinin-based combination therapy (ACT) in all the country. Recently seasonal malaria chemoprevention has been implemented in the northern regions of Benin, where malaria transmission is highly seasonal. New policies are being introduced in the health system through an integrated national strategic plan oriented towards the elimination of HIV/aids, tuberculosis, malaria, viral hepatitis, IST and diseases with epidemic potential (2020-2024).  

In line with World Health Organization (WHO) recommendations, Benin NMCP’s is now poised to define ways to maximize the future malaria control strategies impact, reduce inefficiencies and create a platform to sub-nationally target resources and monitor progress.  

During this PhD, the candidate will use more information than morbidity and mortality data, human, mosquito and parasite data, which reflect diverse transmission dynamics influenced by climate, environment and behavioral factors to accurately and reliably develop appropriate malaria risk stratification; The candidate will then use mathematical modeling to assess technical feasibility and determine which intervention mixes would maximize impact to meet the target and within the constraint of cost-effectiveness. 

Topic 6 : Building predictive models of malaria vector larval habitat locations for understanding the spatial determinants of malaria transmission in Mozambique  

Vector control remains the vital component of malaria control and elimination strategies. A potentially important target of vector control for malaria is the larva. It is well recognized that proper management of larval habitats in sub-Saharan countries, particularly during dry seasons, can help suppress vector densities and malaria transmission. However, our understanding of the ecology of malaria vector larvae is still limited. For example, in Mozambique little is known about the causes of spatial heterogeneity in the abundance and distribution of malaria vectors, as well as several larval habitats contributing to malaria vector abundance.

Mechanistic and predictive models that make use of landscape variables and account for seasonal variations in habitat probability based on accumulated precipitation are essential tools for investigating the links between larval habitat distribution and adult malaria vector distribution across a large landscape where manually mapping the larval habitats would be infeasible. Also, such models could be useful for malaria control programs, allowing decision-makers to focus their efforts to areas where larval habitats are most likely to occur.

Therefore, this project proposal intends to develop geospatial and mechanistic models tailored to answer the following objectives: (1) to characterize larval habitats of the malaria vector; (2) to investigate the spatial distribution of the malaria vector by determining the links between the distribution of larval habitats and the distribution of the adult vector of malaria in different geographic landscapes; (3) make use of the information generated to develop and test predictive models of larval habitat sites using landscape variables that predict the likelihood of water bodies, and taking into account the seasonal changes habitat probability based on accumulated rainfall; (4) then investigate how the distribution larval habitats is linked to the current spatial heterogeneity of malaria prevalence in the country.

The successful candidate would be based at Manhiça Health Research Centre (CISM), with secondments at Eduardo Mondlane University (UEM), University of Johannesburg (UJ) and NMCP.   The candidate should have MSc in Mathematics/Statistics or any related field with strong mathematical/statistical background, with knowledge of programming and statistical software (preferably R), basic knowledge of relational database systems and SQL, knowledge of malaria epidemiology, effective communication and scientific writing skills, and good interpersonal and organization skills.

Topic 7 : Mathematical modeling and control of malaria transmission dynamics: Using sterile mosquito dissemination by Wolbachia bacteria in Burkina Faso  

Given that Anopheles mosquitoes are malaria vectors, one of the effective strategies to control malaria transmission relies on the use of insecticides. Accordingly, resistance to insecticides has emerged as a biological threat to malaria control and elimination efforts in endemic areas. Widespread insecticide resistance has increased the malaria burden in many malaria-endemic regions, challenging global malaria eradication. Thus, an effective alternative to insecticides is needed. Notably, the sterile insect technique, in particular the Wolbachia bacteria. The sterile insect technique consists in a massive releasing into the wild of sterilized males to mate with females in the aim to reduce the size of the insect population. It has been first studied by R. Bushland and E. Knipling  and experimented successfully in the early 1950’s by nearly eradicating screw-worm fly in North America. Since then, this technique has been studied on different pests and disease vectors. In particular, it is of interest for control of mosquito populations and has been modeled mathematically and studied in several papers. So, in the research project, we are interested in the development of a mathematical model of the dynamics of mosquito populations subject to human interventions by ODE’s (Ordinary differential equations). Our main goal is the elimination or the reduction of wild mosquitoes under a certain threshold in a targeted area by the release of sterilized males. In this case, it will be a question of establishing a relation between this critical threshold for the release of inseminated mosquitoes and the basic reproduction rate. Thus, our analysis will allow a better understanding of the effectiveness of this technique in the fight against malaria diseases. 

Numerical analysis and computer simulations will be undertaken to put theory and observation together to gain insight into the working biological systems, to estimate relevant parameters from data and validate the proposed models. Those numerical simulations will show the impact of sterile mosquitoes on malaria transmissions global behavior and reveal the effects of time on the persistence and extinction of the disease. 

A successful candidate would be expected to spend time TARGET Malaria team in Bobo Dioulasso to learn advanced biological techniques about virus Wolbachia and will have access to a comprehensive library to start their work.  

Successful candidate must have a good background in mathematical modeling and numerical simulation. 

Successful candidate would also contribute through his numerical simulations results to local capacity building to improve uptake of modelled work in decision making processes. 

Topic 8 : Molecular surveillance of malaria coupled with mathematical modelling to assess asymptomatic infections in Kenya  

In this PhD, the candidate will dive deep into understanding the molecular and sero- surveillance system for malaria in Kenya, specifically the different data collected, consisting of various indicators about malaria burden, intervention deployment, as well as geography-specific data (e.g., seasonality). First, using various statistical methods, the candidate will analyse the historical time series and quantify the effects of deployed interventions over time. The results of this analysis will be subsequently used to parameterise an individual-based model of malaria transmission reproducing the malaria transmission dynamics at various administrative levels across the country. This model will allow analysis of several scenarios investigating the potential impact of alternative control interventions. Specifically, the PhD will entail: 

• Using statistical methods to conduct descriptive analysis of the available molecular and sero-epidemiological data in order to understand the evolution of the local malaria situation. 
• Modelling malaria transmission and the effects of malaria control interventions in Kenya and conducting scenario analysis to predict reduction of asymptomatic infections 
• Communicating results of analyses and supporting the NMCP in formulating interventions. 
• Relate  and assess the developed  model with data from other African countries such as Rwanda and Benin.
• Master’s Degree in Molecular biology and Bioinformatics, epidemiology, immunology, or any other public-health-related or quantitative topic with experience in working on infectious diseases 

Topic 9 : Real-time prediction of insecticide resistance in Rwanda  

Successful malaria control depends on the use of insecticide products in long-lasting insecticidal nets and indoor residual spraying. Using these methods, Rwanda has successfully reduced the numbers of cases and deaths due to malaria. However, the effectiveness of these interventions is threatened by the rise and spread of insecticide resistance (IR), which has increased rapidly across malaria-endemic Africa over the past decade and risks undoing the significant gains in controlling malaria cases across the continent. Accurate monitoring and rapid response can enable mosquito control programs to adapt the use of insecticides to mitigate or even prevent the rise of resistance.    The project will develop a predictive modelling tool to pre-empt the development of insecticide resistance and enable the MOPDD, and other malaria control departments in Africa, to respond effectively to the threat of insecticide resistance. The candidate will work closely with the Rwandan National Malaria Control Program (Malaria & Other Parasitic Diseases Division; MOPDD), AIMS Rwanda, and the Malaria Atlas Project in Perth, Australia.  They will adapt and extend a cutting-edge mathematical and statistical model of phenotypic insecticide resistance, to enable spatio-temporal prediction of insecticide resistance levels in target vector species from genotypic (e.g., KDR marker) and phenotypic resistance, and resistance intensity bioassay data all held by MOPDD, along with environmental data on e.g., agricultural insecticide usage and climate. The model fitting process will elucidate the likely drivers of resistance in Rwanda. The insecticide resistance prediction maps produced will provide an evidence-base to inform MOPDD in switching between different intervention types. The model will also map uncertainty in predictions, enabling prioritization of future IR surveillance activities.  The candidate will develop computational code enabling this model to be rapidly re-run as new data is collected, and results uploaded to a dashboard to inform the Ministry of Health/MOPDD in real-time. This computer code will be packaged into a user-friendly research software application enabling the tool to be used in other countries, and beyond the end of the project.    Required: 

• MSc in either Mathematics/Statistics (or any related field with strong mathematical/statistical background) or in Biosciences but with experience in data analysis 
• Experience using statistical software, preferably R 
• Knowledge of malaria epidemiology or mosquito biology 
• Good communication and scientific writing skills 
• Good interpersonal and organisation skills 

Topic 10 : Mechanistic and geospatial models to support genomic surveillance in elimination countries such as Senegal  

In many elimination settings common surveillance datasets such as cross-sectional surveys lack the statistical power to inform sub nationally tailored intervention strategies, especially when trying to push the final frontier of malaria to zero. The integration of genomic/molecular surveillance into routine surveillance activities has the potential to increase the actionable intelligence for making programmatic decisions on optimal mixes of interventions for elimination by informing on drug and diagnostic resistance; identifying reservoirs of sustained transmission; quantifying importation risk and identifying local transmission foci whilst additionally supporting impact evaluations. 

This project would focus on the integration of novel streams of genomic data into geospatial and mechanistic approaches. A successful candidate would partner with current genomic experts to understand relevant data sources, hierarchical structures and how they inform current geospatial modelling frameworks, with a view to developing/using statistical and mathematical techniques synthesising genomic and other data to answer operationally relevant research questions as identified by a partner national program. This work would be in partnership with genomics researchers and national programs in Senegal. 

Topic 11 : Impact and risk of deployment of Seasonal Malaria Chemoprevention in Mozambique  

Seasonal malaria chemoprevention (SMC) is a highly effective community-based intervention for malaria prevention in areas where the malaria burden is high and seasonal transmission occurs. To date, mainly west African countries have been considered for implementation due to their strong seasonality of transmission. SMC had not been previously implemented in east and southern Africa due to concerns over parasite resistance to the antimalarials used in SMC. Mozambique contributes 4% of global malaria cases, and malaria represents one of the four major causes of death in the country.  

However, Mozambique has a very high number of malaria cases in some parts and it is believed that SMC would have a strong impact, due to its rainfall patterns concentrating malaria cases during well-defined periods. The High Burden to High Impact initiative launched in 2018 promotes the use of evidence to support national malaria strategies. In this light, dynamical modelling can serve as a useful tool to provide insight and simulate what would be the expected impact of SMC in untested areas. Based on recommendations in the midterm review of the Malaria Strategic Plan, Malaria Consortium, in partnership with the Mozambican National Malaria Control Program (NMCP), initiated a two-year SMC implementation evaluation in the northern province of Nampula. These studies showed high levels of effectiveness, while resistance was also high, but not negatively impacted by SMC. 

Often, the counter-arguments for using drug-based interventions include the risk of adding drug pressure and increasing the risk of emergence and spread of drug-resistant Plasmodium falciparum. Indeed, it has been assumed until now that drug resistance would render the intervention ineffective but no real world evidence has been collected to date. So here again, modelling can help quantify what this risk could be expected to be given specific deployment and geographic characteristics. 

In order to explore all these aspects, the project would be articulated around the following objectives. 

• Simulate current epidemiology and burden of malaria in Mozambique  
• Explore the impact of SMC in different parts of the country and for different implementation regimens 
• Explore the effectiveness of SMC as a result of potential emerging resistance in Mozambique. 

Prior experience or study in at least one of the following will be required: 

• mathematical or statistical modelling (in any quantitative discipline) 
• quantitative analysis in infectious disease epidemiology 
• quantitative population ecology 

The following specific skills and experience are desirable: 

• programming skills in R 
• malaria chemoprevention 
• epidemiology of mosquito-borne diseases 

Idealism, humility, and desire to see quantitative approaches make a difference in the world 

Topic12: Biophysical Modelling of Malaria Parasite invasion of Red Blood Cells

The asexual proliferation of merozoite (malaria parasite) inside human red blood cells (RBCs) has devastating effects on human health. When merozoites enter the bloodstream from the liver, they must invade RBCs within a few minutes to survive. Thus understanding the invasion mechanism is critical to fighting the disease.

The merozoite generates force using actin and myosin, but in a different way to other cells, using a ring structure unique to apicomplexa. Detailed positions of protein complexes involved are still not well established but from a physics perspective it is necessary that actin filaments and myosin motors are attached to a rigid structure, one in the RBC and one in the merozoite. This enables the myosin motors to push the merozoite, sliding it with respect to the RBC. To invade, the merozoite needs to get through the RBC spectrin network on the inside of its membrane.

In this project the candidate will be based at AIMS Ghana and will calculate the active propulsion force generated by the merozoite that is necessary for successful invasion. This will involve developing a simple model of the molecular components and calculating the energy required to make a hole in the RBC spectrin network by stretching and breaking bonds. We expect only a few filaments are required, meaning that the stochastic fluctuations inherent in the system will be important in determining whether or not a merozoite successfully invades. We will model the stochasticity of motor binding using master equations and disorder in the spectrin network using disordered polymer network theory. We will validate our model and test predictions with experimental images taken by our WACCBIP (University of Ghana) collaborators. This will enable us to determine the spatial arrangement, identities and numbers of cytoskeleton components and inform target choice for future antimalarial drugs or vaccines. Through regular meetings with the Ghanaian National Malaria Control Program (NMCP) team, we will tailor the development of the modelling work and target choice to best address the NMCP goals.

Requirements:

• Masters Level Degree (e.g. MSc) in Physics or Mathematics (or any related field with a strong mathematical background)
• Good interpersonal and organization skills 
• Experience in programming &/or using mathematical software 
• Some knowledge of cell or molecular biology is an advantage

PhD Students

Alfredo Zacarias Muxlhanga

Read More… from Mamodafrica Phd program

Fameno Rakotoniaina

Gabriel Michel Monteiro

Roland Christel Sonounameto

Timóteo Sambo

Download Call for Applications

Apply for Mamodafrica Phd program

ALL RIGHTS RESERVED | AIMS 2024 |

Bryan Bryson

Adjunct associate professor in the department of immunology and infectious diseases, disease: tuberculosis.

Research : The Bryson lab is working to determine how cells of the immune system control and eliminate one of the world’s most deadly pathogens, Mycobacterium tuberculosis (Mtb).

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