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Doctor of Philosophy in Software Engineering

Program description.

The PhD in Software Engineering program is tailored to the student. The student must arrange a course program with the guidance and approval of a faculty member chosen as their graduate advisor. Adjustments can be made as the student’s interests develop and a specific dissertation top is chosen.

The software engineering researchers in the Department of Computer Science are focused on issues related to effectively developing large-scale, complex systems. In particular, new categories of applications are emerging such as big data, cyber physical, and autonomous adaptable systems, which continue to drive leading edge research in software engineering on diverse topics. Key research areas include requirements engineering, architecture, design, service-oriented computing, testing and verification, static analysis, software maintenance and multi-agent systems.

Career Opportunities

Virtually all major companies and corporations need software related core competencies. Software engineers are central in developing and making use of these competencies. They work in teams that interface extensively with clients, company executives, IT managers, data scientists, security and domain experts.

Software engineering professionals are creative, highly collaborative, well paid, and in very high demand with employers. Graduates of the program seek academic positions at universities, as well as positions as researchers, senior software engineers and data scientists. Graduates often become industry experts in various fields like cybersecurity, artificial intelligence, machine learning and natural language processing.

Marketable Skills

Review the marketable skills for this academic program.

Application Requirements

Test score required:  Yes

Deadlines:  University  deadlines  apply.

Admission Option One

• Degree requirements:  A master’s degree in computer science or its equivalent
• GPA:  Minimum of 3.5
• Test score:  Minimum revised GRE scores of 308, 153, 155, and 4 for the combined, verbal, quantitative and analytical writing components, respectively, are advisable.

Admission Option Two

• Degree requirements:  A BS degree in related area that includes two semesters of calculus and linear algebra.
• GPA:  Minimum of 3.5 in the last 60 semester credit hours.
• Test score:  Minimum revised GRE scores of 315, 156, 159 and 4 for the combined, verbal, quantitative and analytical writing components, respectively, are advisable.

Applicants are admitted on a competitive basis.

Contact Information

Admissions Email: [email protected]

Shyam Karrah Email: [email protected] Phone: 972-883-4197 Office: ECSS 4.704 Website: personal.utdallas.edu/~skarrah

Erik Jonsson School of Engineering and Computer Science The University of Texas at Dallas, ECW41 800 W. Campbell Road Richardson, TX 75080-3021 Email: [email protected]

cs.utdallas.edu engineering.utdallas.edu

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Software Engineering Ph.D. Program

Software and societal systems department, build it better....

Software is becoming ever more important to our daily lives, as well as every sector of industry.  But as software systems increase in capability, they increase in complexity, resulting in delays, defects, and vulnerabilities.

Our Ph.D. program in Software Engineering seeks to educate the next generation of high-impact software engineering research, development, and educational leaders who will solve the problems associated with building large-scale and critical software systems.  Learn about our groundbreaking research , our world-leading faculty , and our alumni who are already making a big difference in the world.  We hope you will apply  to our Ph.D. program  so you can join us in learning to build software better!

Don't Forget!

Applications to the Ph.D. program in Software Engineering are accepted every year with a deadline in  December. This year the application window is open  September 4th, 2024, Early Deadline of November 20th, 2024, and final Deadline of December 11th, 2024. 

Learn how to apply

• Why Software Engineering?
• What are your research strengths?
• What will my course of study look like?
• What are the prerequisites for admission?
• How is this program going to help my career?
• How do I apply?

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Our faculty are taking on some of the most exciting technical challenges modern software faces. Learn more about their work in these short research vignettes!

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Software Engineering (PhD) Doctor of Philosophy

Quick facts.

of all Higher-Ed Institutions

- Center for World University Rankings, 2022

In Best Value Among Arizona's Public Universities

- Payscale, 2022

The University of Arizona's College of Engineering has launched the Software Engineering PhD degree in response to the high demand for individuals trained in the software engineering discipline. The degree program is critical in driving student success in a rapidly changing world and tackling essential problems at the edges of human endeavor. 

As a student graduating with a PhD in Software Engineering, you will be better positioned to develop the skills and mindsets to be leaders in software development, computing, machine learning, ever-increasing automation and connectivity, human and intelligent systems, data science, and network sciences.

Through the PhD program, you'll demonstrate the ability to design, develop, test, integrate, and evaluate software applications/products/systems in diverse computing and engineering domains. You'll also be able to critically analyze and review published research results and other literature related to your area of study. You'll also demonstrate your ability to articulate all aspects of the research in your software engineering specialization area, describe and defend the significance of your work, explain your research methodologies, and summarize your findings. 

The global software engineering market alone will be worth $64 billion by 2025, and it is a vital part of a larger industry. Some factors behind this growth include increased automation in multiple sectors, the demand for cloud-based solutions, the Internet of Things, and an increased number of devices that can be used in daily life for convenience. Thus, pursuing a Software Engineering PhD will give you a competitive edge in this fast-growing industry.

No GRE is required for this graduate degree program.

A minor is required for this program and will be determined by the student and advisor.

Students who do not have a degree equivalent to the University of Arizona Bachelor of Science degree in a computing-related program may be admitted into the graduate program but may be required to complete additional graduate-level pre-requisite courses prior to enrolling in some graduate courses. 

Proficiency in one or more programming languages OR one to two years of industry experience in a software-related position is required.

*Residents of some U.S. Territories may not be eligible. Please see our Eligibility & State Authorization page for more information.

Courses for this program include: 

SFWE 502: Software DevSecOps

This course will allow you to explore key principles of a DevSecOps approach to software development. Development (Dev) and operations (Ops) are the union of people, processes, and technology to continually automate and develop higher-quality/more reliable software products faster. Security (Sec) is integrated into a typical DevOps pipeline to address potential security issues in code as soon as possible in the software development lifecycle.

SFWE 503: Software Project Management

In this course, you will learn how to plan, track, and communicate the status of large-scale software projects to a diverse group of stakeholders. Using modern traditional and Agile software development methodologies and tools and emulating a realistic software development project, students will be immersed in the activities used by industry to develop, manage, and monitor software product development throughout the semester. You’ll learn why planning a software project is important, what constitutes a good plan, how to adapt to the unexpected and unknowns that are likely to occur throughout the project development, and how to track and share the status of the project with your team members, other teams, and the customers/business managers.

SFWE 504: Software Requirements Analysis & Test

Learn how to derive and develop software requirements that are measurable, testable, and lead to a compliant software design and implementation. Using industry best practices and tools, you will learn how to elicit, analyze, specify, and validate functional requirements (what should the software system do) and non-functional software requirements (how should the software system fulfill the functional requirements). You will develop software requirement models and specifications that capture the customer/user's needs.

SFWE 505: Software Architecture & Design

In this course, you'll explore different architectural styles and patterns and learn to apply modern processes, methods, and tools in architecting, modeling, and designing software systems. They will also learn the importance of developing a sound software architecture as part of the overall software design.  

SFWE 506: Distributed Computing

In this course, you will explore the unique aspects and considerations required to develop a large-scale software product in a distributed computing environment. Distributed computing refers to a system where processing and data storage are distributed across multiple devices or systems rather than being handled by a single central device. In a distributed system, each device or system has its own processing capabilities and may also store and manage its own data. 

SFWE 507: Foundations of Software Engineering

Gain foundational skills and knowledge used by software engineers in diverse industries. The course introduces you to the different software development lifecycle (SDLC) phases used in developing, delivering, and maintaining software products for a wide variety of applications. Common software process models will be introduced, along with developing an understanding of the importance of defining software requirements, developing software architectures and designs, and the various forms of testing that go into delivering reliable and resilient software systems.

SFWE 509: Cloud Computing Principles and Practices

This introductory course on cloud computing delves into the fundamental technologies and ideas that make up contemporary cloud computing infrastructure. You'll get hands-on practice using cloud service models (IaaS, PaaS, SaaS, FaaS), virtualization, data centers, cloud management, and essential Linux commands. The course also covers advanced topics such as cloud storage, containers, microservices, serverless computing, cloud security, emerging trends in cloud IoT, mobile clouds, edge computing, and big data processing.

SFWE 510: Cloud Native Software Engineering

This course introduces the design and implementation of decentralized systems with up-to-date software architecture and relevant development frameworks. Topics include inter-module communication, asynchronous processing, security, concurrency, parallelism, and an overview of contemporary enterprise technology and challenges. The course also dives into the development, infrastructure, best practices, and DevOps practices for monitoring and debugging such systems.

Earning your Doctor of Philosophy in Software Engineering (PhD) will build core skills, including:

• Agile methodology
• Algorithm design & optimization
• Artificial Intelligence
• Cloud & distributed computing
• Continuous deployment
• Continuous integration
• Cybersecurity practices & standards
• Full stack development
• Machine learning algorithms & approaches
• Programming language proficiency
• Software Development Lifecycle
• Software engineering

Potential Career Paths

Graduates of the Software Engineering PhD program will be prepared to pursue careers in the following fields, among many others:

• Artificial Intelligence/Machine Learning
• Aerospace & Defense
• Space Exploration
• Data Science & Analytics
• Medical Devices Technologies
• Financial Systems & Technologies
• Quantum Computing
• Automotive/Vehicle Networking/Autonomous Driving
• Cybersecurity Analysis
• Engineering
• Systems & Software Solutions Architecture
• Mobile Computing
• Computer Vision
• Cloud Computing/Networking

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How to Apply

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Ph.D. - Computer Science and Software Engineering

Why this degree.

The Doctor of Philosophy program in Computer Science and Software Engineering offers a unique opportunity for doctoral students to develop research and development skills in cutting-edge computer science and software engineering disciplines. We cater to doctoral students with an outstanding aptitude and strong research skills in computer science and software engineering. A dissertation embodying the results of this research represents the major portion of the requirements for this degree. Four calendar years beyond the bachelor’s degree or three past the master’s degree are usually needed to complete the Ph.D. program.

You are eligible to apply if...

• You hold a Bachelor's degree or a master's degree in Computer Science, Software Engineering, Cybersecurity Engineering or equivalent from an institution of recognized standing
• Your GPA is 3.0 or above
• Your GRE general exam combined score is at least 300, with a verbal score of at least 150, a quantitative score of at least 150; and a written score of at least 3.
• If you are an international student, your TOEFL iBT score should be at least 79, with a minimum of 16 on each of four component parts (reading, listening, speaking, and writing) or, IELTS score of at least 6.5.

To complete the program you must...

• Take a minimum of 66 credit hours of graduate work past the bachelor’s degree.
• All the courses except COMP8990 must be graded courses, among which three (i.e., COMP7270, COMP7300, and COMP7500) are required core graduate courses for a total of nine (9) credit hours.
• (i) formal COMP courses (minimum 21 credit hours) and/or
• (ii) other elective courses (up to 9 credit hours) at 6000 level or higher is required.
• May take up to six (6) credit hours of directed study (i.e., COMP7930/8930).
• Take at least one additional COMP course at 7000 level or higher (excluding COMP7930/8930).
• Take at least 18 credit hours of COMP 8990 Research and Dissertation.
• (i) the “PhD Qualifying Examination” and
• (ii) the “PhD General Oral Examination”. The PhD Qualifying Examination will be successfully fulfilled by passing the three qualifying exams (i.e., computer organization/architecture, operating systems, and algorithms) or earning a B or higher in required remedy courses.
• Prepare an acceptable dissertation reflecting high achievement in scholarship and independent investigation.
• Pass a Final Oral Examination defending the dissertation.

Doctoral students must meet the following repeating-courses requirements:

• Students who have taken a 5000-level course at Auburn University may not take the 6000-level equivalent for credit.
• Doctoral students may not take more than six hours of Directed Study (i.e., COMP7930/8930).
• Special Topics (i.e., COMP7970/8970) may be repeated provided each entails a change in topic.
• Dissertation and Research, COMP8990, may be repeated, but only a maximum of 18 hours count toward the Ph.D degree.

What can you expect?

• Xiao Qin, graduate program officer — [email protected]
• Clint Lovelace, manager of academic programs — [email protected]
• Faculty Information: http://www.eng.auburn.edu/comp/faculty
• https://www.slideshare.net/xqin74/auburn-csse-graduate-student-orientation

Applying for the Ph.D. - Computer Science and Software Engineering

• Fill out the online graduate application at https://graduate.auburn.edu/prospective-students/application-instructions/ (you will be required to create an account)
• Upload your GRE scores, official transcripts, statement of purpose, resume, and three recommendation letters
• Upload your TOEFL or IELTS scores (For International Students)
• For more information, visit http://www.eng.auburn.edu/comp/academics/graduate

• Chancellor’s Message

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2024-25 edition, software engineering, ph.d..

A new code search engine. New insights into how trust emerges (or doesn’t) in distributed software development organizations. New visualizations to aid developers in debugging code. New lessons about the quality of open-source components. A new Internet infrastructure that enables secure computational exchange.

These are just some examples of the wide variety of projects being worked on by current Ph.D. students in the software engineering Ph.D. program at UC Irvine.

As software continues to transform society in dramatic and powerful ways, we must improve our ability to reliably develop high-quality systems. From early incarnations as just an idea or set of requirements to when software is actually built, deployed and customized in the field, many challenges exist across the lifecycle that make creating software still a non-trivial endeavor today.

The software engineering Ph.D. program offers students the opportunity to tackle these challenges, whether it is through designing new tools, performing studies of developers and teams at work, creating new infrastructures or developing new theories about software and how it is developed. No fewer than six faculty members bring a broad range of expertise and perspectives to the program, guaranteeing a diverse yet deep education in the topic.

A strong core of classes introduces students to classic material and recent innovations. At the same time, we focus on research from the beginning. New students are required to identify and experiment with one or more research topics early, so that they can become familiar with the nature of research, write papers, attend conferences and begin to become part of the broader software engineering community. This focus on research naturally continues throughout the program, with an emphasis on publishing novel results in the appropriate venues.

For additional information about this degree program, please see: https://www.informatics.uci.edu/grad/phd-software-engineering/

Program of Study

Pre-candidacy course requirements.

Students must complete a software engineering core course, five elective courses, and at least three quarters of individual study and/or thesis supervision courses. Students must take additional courses of their own choosing or additional individual studies, in order to fulfill 48 units before advancement to candidacy. The selection of courses should form a coherent educational plan to be approved by the student's faculty advisor.

All five elective courses must be regular, 4-unit courses from the SWE 2XX series. Individual study, thesis supervision, and seminars do not qualify as electives.

The selection of courses should form a coherent educational plan to be approved by the student's faculty advisor.

The student's faculty advisor is responsible for ensuring this requirement is met.

Qualifying Examinations

Research Assessment

Students must find a faculty advisor and successfully complete a research project with that faculty member. The research project should be done over at least two quarters of independent study with that faculty member. The goal of this research assessment is to introduce the student to the practice of scientific publication.

Based on the project, the student must produce a research paper of publishable quality. This research paper must be reviewed by three faculty members in a peer-review process, revised by the student, and approved by the three faculty members.

The research assessment is graded Ph.D. PASS, M.S. PASS, or FAIL. In case of M.S. PASS or FAIL, the student can re-submit the paper at most one more time within the maximum period of six months. A second M.S. PASS or FAIL results in disqualification from the doctoral program.

Advancement to Candidacy Examination

Each Ph.D. student must pass the oral advancement to candidacy exam, which assesses the student’s ability to conduct, present, and orally defend research work at the doctoral level. The research project and paper are the basis for the student’s oral advancement to candidacy exam. The oral candidacy exam consists of the research presentation by the student, followed by questions from the candidacy committee.

The student must complete the course requirements, and pass the research assessment prior to advancing to candidacy. The candidacy committee will consist of five faculty members, the majority of whom must be members of the student’s program, and is conducted in accordance with UCI Senate regulations.

Dissertation Topic Defense

The student must present a carefully articulated document representing the student’s dissertation plan. This document must include the proposed dissertation abstract, a discussion of the approach, a comprehensive survey of related work, and a plan for completing the work. The dissertation plan is presented by the student to the dissertation committee, who must unanimously approve the student’s proposal. The dissertation defense committee is formed in accordance to UCI Senate regulations.

Doctoral Dissertation and Final Examination

Students are required to complete a doctoral dissertation in accordance with Academic Senate regulations. In addition, they must pass an oral thesis defense which consists of a public presentation of the student’s research followed by an oral examination by the student’s doctoral committee. The committee must approve the thesis unanimously.

The normative time for advancement to candidacy is three years. The normative time for completion of the Ph.D. is six years, and the maximum time permitted is seven years.

Requirements Beyond Graduate Division Minimum Requirements

All Ph.D. students are expected to maintain a minimum GPA of 3.5 throughout the program. Failure to maintain this minimum will result in a recommendation that the student be disqualified. In addition, no grade lower than a B is counted toward satisfying any course requirements.

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SoftwareDegrees.org

PhD in Software Engineering Programs

On This Page:

Take your education to the highest peak with our PhD in software engineering guide! This real-world resource will help you understand how doctoral programs in software are structured & delivered. Learn about admissions, coursework, research, and dissertation requirements. Take a closer look at PhD program costs, online learning opportunities, and the career benefits of earning a doctorate in software engineering. And find answers to frequently asked questions from potential students.

Have you already decided on a doctorate? Skip ahead to our state-by-state listings of PhD in software engineering programs !

What is a Doctorate in Software Engineering?

A PhD in software engineering transforms great software engineers into field experts. PhD programs allow students to immerse themselves in advanced focus areas such as software organization and properties, notations and tools, and creation and management. In addition, doctoral students complete original and detailed research in order to become a go-to expert on their dissertation topic.

A doctorate in software engineering is a top-level educational qualification. Professionals who pursue this path usually plan to become university professors, high-flying researchers in major tech companies, and well-paid consultants. Before you commit to 4-5 years of hard work, it’s worth knowing where you’re headed.

Software Engineering PhD Programs: Your Degree Options

Phd in software engineering.

A PhD in software engineering has a two-fold purpose. It hones your ability to engineer efficient and practical software systems. But it also challenges you to consider the theories behind software development, study its applications, and develop new tools. In doing so, you’ll be prepared to:

• Lead research and development teams in advancing software architecture
• Teach software engineering (and pursue tenure) at the university level
• Assume executive positions responsible for top-level software-related decisions

PhD in Software Development

A PhD in software development prepares you to apply advanced problem-solving techniques to the field of software. You’ll design, develop, validate, and maintain large software applications and work with the latest technologies. Like PhD in software engineering candidates, most software development PhD graduates pursue university-level teaching jobs and research-focused industry positions (e.g. senior or principal software developer).

PhD in Computer Science with a Software Engineering Concentration

A PhD in computer science with a software engineering concentration will provide you with the research skills to advance software systems through computational theory, algorithmic research & development, and/or practical design innovations. PhD graduates play a lead role in advancing cutting-edge technologies like Artificial Intelligence (AI). They also apply for software engineering & computer science faculty positions at colleges and universities.

PhD Program Overview: Curriculum, Admission Requirements & Costs

Structure & timeline.

Have a look at the curriculum links in our listings to get a sense of how a doctorate is structured. PhD programs in software engineering consist of core courses, electives, research, and a dissertation. They typically take four or five years to complete.

• Years 1-3: At most universities, doctoral students in software engineering complete core requirements and electives in the first two or three years of the program. During this time, you will also select a dissertation topic, develop a proposal, and defend your plan in a public setting. PhD students earn candidate status once the proposal is approved.
• Years 4-5: PhD programs become research-heavy in the final two years. You should expect to spend a couple of years conducting research and writing your dissertation. A faculty advisor will help guide you through the dissertation process, providing advice on topic selection, assistance with research, and prep for your dissertation defense. At the end of the program, you will publicly defend your findings in front of a faculty dissertation committee.

PhD in Software Engineering: Curriculum

Core coursework & electives.

Software engineering PhD programs contain core coursework and electives, with specific credit mandates. Each school will allow you to explore different topics, easing the process of creating an impactful and motivating dissertation proposal. Advisors will tailor your coursework to help you discover and focus on your specialization.

For example, a PhD in software engineering from the University of California Irvine has a 48-credit coursework requirement, consisting of:

• The software engineering core
• Five electives in software engineering topics
• Three courses of individual study and/or thesis supervision
• Additional coursework to fill in credits toward the 48-credit requirement
• Attending dozens of seminars

A PhD in software engineering from Carnegie Mellon features:

• One core research course in software engineering
• Four “star” and two elective courses, each selected by the student
• A practicum
• Two semesters as a teaching assistant serving as an assistant teacher

North Dakota State University’s software and security engineering PhD program contains:

• Six core courses
• One of two focus tracks in either software engineering or cybersecurity, each requiring three courses
• The doctoral dissertation

You’ll notice that some PhD in software engineering courses overlap with subjects that have been addressed in master’s programs. The difference is that doctoral courses are much more in-depth. Top-level coursework completed within PhD programs can include:

• Models of software systems
• Type systems for programming languages
• Cloud and security foundations
• Optimizing compilers for modern architectures
• Global e-business strategy
• Information security and privacy
• Human aspects of software development

Research & Dissertation Preparation

While you’re tackling courses, you’ll also be exploring possible research ideas for your dissertation. This phase of your PhD in software engineering can cover a large range of topics. You may wish to investigate advanced areas in software such as:

• Software architecture and design
• Security and privacy
• Analysis and quality assurance
• Developer tools
• Management and organization of software development

Faculty members will help you break down these general categories into an impactful & targeted research topic for your PhD dissertation. You must receive approval for your dissertation topic before you are allowed to complete the last few years of your doctorate.

Be prepared to hit the ground running. Research work will usually begin in the early stages of your doctoral program. The University of California Irvine and Carnegie Mellon specifically mention working on research projects at the onset of the PhD. Some schools even provide directed study opportunities. Directed study allows you to conduct research under the oversight of a faculty member in preparation for your dissertation.

Dissertation

Software engineering PhD students are required to conduct original research that will explore new territory and broaden the industry’s knowledge of the field. You’ll be expected to present your conclusions & findings in a written and publicly defended dissertation. Carnegie Mellon’s handbook offers a thorough account of the dissertation process, from the proposal to its ultimate defense.

Once you have decided on a dissertation topic, completed your research, and created your dissertation:

• A committee of several faculty members involved in your doctoral work will review your written work.
• You will then be required to defend your findings in an oral presentation. A dissertation defense takes approximately 45 minutes, followed by questions.
• The committee can decide to approve—either with or without corrections—or reject the dissertation.

Wondering what a dissertation in software engineering looks like? Examine the following completed dissertations by PhD candidates at UC Irvine and Auburn University:

• Reusable Method Summaries for Improving Performance of Dynamic Dependence Analysis by Vijay Krishna Palepu (PhD graduate from the University of California Irvine)
• Popularity-Aware Storage Systems for Big Data Applications by Ting Cao (PhD graduate from Auburn University)

PhD Admission Requirements

Admission requirements to software engineering PhD programs vary by school. However, you can expect to see most (if not all) of the following listed in university doctoral admissions guides:

• Master’s Degree in a Related Field: Common MS majors include software engineering, computer science, software development, etc. (Some schools will consider BS applicants).
• High GPA: Universities will usually ask for a minimum 3.0 GPA at the undergraduate and graduate levels.
• Competitive GRE Scores
• Personal Statement:  Universities will want to know about your interests, goals, and/or professional experience.
• Letters of Recommendation
• Proof of Proficiency in English: International students from non-English speaking countries may need to take a IELTS or TOEFL test.

Admission to PhD in software engineering programs is highly competitive, so be aware that schools will be considering other aspects of your background. For example, UC Irvine reviews design portfolios, GitHub profiles, and any relevant writing (e.g. scholarly papers).

Tuition Costs & Funding for Software Engineering PhD Programs

It’s important to note that most PhD programs in software engineering are fully funded. If you are considering a doctorate in a STEM field, be sure to ask if tuition is covered. For example:

• The University of Michigan-Dearborn’s PhD in Computer and Information Science (CIS): Software Engineering Concentration follows the university’s fully-funded PhD model.
• PhD candidates earn a tuition waiver and monthly stipend, plus health insurance, in exchange for their work as a graduate student instructor or research assistant (or both).

Similar arrangements exist for PhD candidates at UC Irvine and North Dakota State University.

If you are unable to find a fully funded PhD program, you may wish to look into filing a Free Application for Federal Student Aid ( FAFSA ) for graduate students, scholarship and fellowship options, and—as a last resort—private loans. Tuition for non-funded doctorates will vary from school to school, but you can expect to see tuition prices range from $15,000 to north of $50,000 per year.

Online PhD in Software Engineering Programs

Software development needs no lab work and few physical references, so some online PhD in software engineering programs do exist. However, virtual doctorates are still far less common than online BS in software engineering degrees and online MS in software engineering programs .

Examples of online doctoral programs in the field include the:

• Online PhD in Systems Engineering at Colorado State University
• Online PhD in Computer Science with software engineering coursework at the University of North Dakota

These are doctorates from regionally accredited institutions with solid brick & mortar reputations. You’ll be able to view on-campus lectures live or watch recordings afterwards. You can discuss your work in virtual meetings with your faculty advisors. And you can fit your dissertation research around other commitments. Be aware that online PhD programs aren’t usually funded—you may end up paying tuition costs of $800+ per credit.

PhD Career Benefits & Opportunities

What can you do with a phd in software engineering.

A PhD in software engineering makes you the world’s expert on your dissertation topic. You will be acknowledged as a specialist in software engineering & development wherever you go. While your expertise in the field awards you some flexibility in the roles you choose to pursue, there are a handful of opportunities that are tailor-made for software engineering PhD graduates.

University Faculty in Software Engineering : A PhD is the standard requirement for tenured faculty positions. Entering the world of academia will involve a number of responsibilities, including:

• Instructing undergraduate and graduate students on software engineering principles
• Developing new course materials to address advances in software engineering
• Writing grant proposals to fund research into new technologies
• Conducting research to expand the field of software engineering
• Writing white papers and presenting at conferences and seminars

Computer & Information Research Scientists : Computer and information research scientists design new computer architectures to improve network technology, increase computing speeds, and advance data security measures.

Principal Software Engineers : Principal software engineers function as a company’s technical and managerial focal point for software engineering projects. They ensure clients’ satisfaction with the end product and provide executive management updates on budgetary and resource constraints.

Executives or Start-up Founders : Executives and founders create and guide a company’s vision by applying in-depth knowledge of software systems and applications. If you find yourself interested in leading a start-up, then it’s likely you’ve created—or are involved with—a new software technology or product with industry potential.

Industry Experts & Consultants : Legislatures and agencies enforce various compliance requirements to ensure data security. Industry experts serve as consultants to develop and modify policies and regulations. You essentially monetize your knowledge by lending your expertise wherever it is needed.

Salaries for PhD in Software Engineering Graduates

General salaries.

Wondering if earning a PhD in software engineering will have a positive impact on your earning potential? Well, according to Glassdoor, the answer is a resounding “yes.” Software engineers with PhD degrees earn an average of $40,000 more than master’s degree earners. In 2023, PhD in software engineering earners averaged $164,835 per year ($130,041 base pay and $34,794 additional pay), compared to $121,158 per year ($101,096 base pay and $20,062 additional pay) for master’s in software engineering earners .

Big Tech Company Salaries

Large technology companies—like Google and Meta—seek out elite software engineers. These firms pay well to recruit the best candidates, so your chances of being hired increase significantly with a PhD.

Specific Job Salaries

Sources : U.S. Bureau of Labor Statistics (BLS) provided a computer and information research scientist’s salary (updated May 2021). Glassdoor provided all other salary estimates (updated February 2023). Additional pay refers to cash bonuses and profit sharing.

Is a PhD in Software Engineering Worth it?

You’ve reviewed what earning a PhD in software engineering entails, how long it will take, and what it might cost . You’ve considered admissions criteria , carefully reviewing your own background and your odds of gaining entry to a reputable program. Now for the most important question: Is a PhD in software engineering really worth it?

This is a difficult question to answer, as the decision ultimately depends on your professional goals, existing responsibilities, and your budget. To help you decide, we’ve made the case for both sides.

Pros of a PhD in Software Engineering

Earning a PhD in software engineering is worth it if you want to pursue advanced career opportunities that are unavailable to those with an undergraduate or master’s degree. For example, you may wish to:

• Apply for a top Research & Development (R&D) position within global tech companies (e.g. Microsoft or Google)
• Support start-ups who rely on skilled researchers and innovators as they develop new technologies
• Join the academic world in order to lead groundbreaking research while educating future software engineers

If any of the above sound like you, then a PhD in software engineering is worth it.

Cons of a PhD in Software Engineering

Earning a PhD in software engineering is not worth it if you’re not prepared for the obstacles and intense commitment required to complete a doctorate. For example, you may:

• Have existing responsibilities (family, career, etc.) that make dedicating four to five years to a doctoral program an impossibility
• Are unable to secure admission to a fully-funded program and are overwhelmed with the idea of taking on enormous debt in exchange for an advanced degree
• Either have not considered your career goals or are unsure about your interest in the opportunities available to PhD holders

If the above points ring true for you, then a PhD in Software Engineering is not worth it.

PhD in Software Engineering: Frequently Asked Questions

Can you pursue a doctorate in software engineering without earning a master’s degree first.

Yes. Several schools allow bachelor’s degree graduates to apply without first completing a master’s degree. For example:

• University of Texas at Dallas requires a Bachelor of Science in a related field, 3.5 GPA, and strong GRE scores.
• North Dakota State University requires a Bachelor of Science degree, at least three years of full-time professional software engineering experience, and one programming language (C++, C#, or Java preferred).
• Auburn University requires a relevant bachelor’s degree, with computer science, software engineering, and cybersecurity engineering being preferred.

How Long Are Software Engineering PhD programs?

Most doctoral programs require a full-time commitment of four to five years. PhD programs in software engineering are split into two major phases: coursework and the dissertation. PhD coursework requires two to three years of full-time effort. The dissertation typically takes an additional two to three years of research, writing, and defense.

How Are Master’s Degree and PhD in Software Engineering Programs Different?

Master’s degrees and PhD programs are advanced educational qualifications in software engineering, but there are some important differences between them:

• Program Length : A software engineering master’s degree usually takes two years of full-time study; a PhD program requires a full-time commitment of four to five years.
• Coursework : Master’s programs typically require 30 course credits, culminating with a thesis or final project. PhD programs are four to five years long and involve core coursework, electives, and the completion of a PhD dissertation.
• Master’s Thesis vs. PhD Dissertation : A master’s thesis involves analyzing and commenting on existing research in the world of software engineering. A PhD dissertation requires unique research and the development of an original concept. PhD students ultimately contribute new knowledge to the field of software engineering.
• Career Opportunities : A master’s degree in software engineering will provide you with advanced skills required to thrive within software development companies. You’ll be able to apply your in-depth knowledge to create & manage complex software applications through the entire development cycle. A software engineering PhD prepares you to conduct research and educate students within academia or pursue professional R&D positions.

All PhD in Software Engineering Programs

8 Schools Found

Auburn University

Samuel Ginn College of Engineering

Auburn University, Alabama

PhD in Computer Science and Software Engineering

Naval postgraduate school.

Department of Computer Science

Monterey, California

Doctor of Philosophy (PhD) in Software Engineering

Offered Online

University of California-Irvine

Department of Informatics

Irvine, California

PhD Software Engineering

North dakota, north dakota state university-main campus.

College of Engineering

Fargo, North Dakota

PhD in Software and Security Engineering

Pennsylvania, carnegie mellon university.

Institute for Software Research

Pittsburgh, Pennsylvania

Southern Methodist University

Lyle School of Engineering

Dallas, Texas

Doctor of Engineering in Software Engineering

The university of texas at arlington.

Arlington, Texas

Doctorate in Computer Science - Software Engineering Track

The university of texas at dallas.

Erik Jonsson School of Engineering and Computer Science

Richardson, Texas

Invenia Blog

Blogging About Electricity Grids, Julia, and Machine Learning

The Hitchhiker’s Guide to Research Software Engineering: From PhD to RSE

Author: Glenn Moynihan

In 2017, the twilight days of my PhD in computational physics, I found myself ready to leave academia behind. While my research was interesting, it was not what I wanted to pursue full time. However, I was happy with the type of work I was doing, contributing to research software, and I wanted to apply myself in a more industrial setting.

Many postgraduates face a similar decision. A study conducted by the Royal Society in 2010 reported that only 3.5% of PhD graduates end up in permanent research positions in academia. Leaving aside the roots of the brain drain on Universities, it is a compelling statistic that the vast majority of post-graduates end up leaving academia for industry at some point in their career. It comes as no surprise that there are a growing number of bootcamps like S2DS , faculty.ai , and Insight that have sprung up in response to this trend, for machine learning and data science especially. There are also no shortage of helpful forum discussions and blog posts outlining what you should do in order to “break into the industry”, as well as many that relate the personal experiences of those who ultimately made the switch.

While the advice that follows in this blog post is directed at those looking to change careers, it would equally benefit those who opt to remain in the academic track. Since the environment and incentives around building academic research software are very different to those of industry, the workflows around the former are, in general, not guided by the same engineering practices that are valued in the latter.

That is to say: there is a difference between what is important in writing software for research, and for a user-focused, software product . Academic research software prioritises scientific correctness and flexibility to experiment above all else in pursuit of the researchers’ end product: published papers. Industry software, on the other hand, prioritises maintainability, robustness, and testing as the software (generally speaking) is the product.

However, the two tracks share many common goals as well, such as catering to “users”, emphasising performance and reproducibility , but most importantly both ventures are collaborative . Arguably then, both sets of principles are needed to write and maintain high-quality research software. Incidentally, the Research Software Engineering group at Invenia is uniquely tasked with incorporating all these incentives into the development of our research packages in order to get the best of both worlds. But I digress.

What I wish I knew in my PhD

Most postgrads are self-taught programmers and learn from the same resources as their peers and collaborators, which are ostensibly adequate for academia. Many also tend to work in isolation on their part of the code base and don’t require merging with other contributors’ work very frequently. In industry, however, continuous integration underpins many development workflows. Under a continuous delivery cycle, a developer benefits from the prompt feedback and cooperation of a full team of professional engineers and can, therefore, learn to implement engineering best practices more efficiently.

As such, it feels like a missed opportunity for universities not to promote good engineering practices more and teach them to their students. Not least because having stable and maintainable tools are, in a sense, “public goods” in academia as much as industry. Yet, while everyone gains from improving the tools, researchers are not generally incentivised to invest their precious time or effort on these tasks unless it is part of some well-funded, high-impact initiative. As Jake VanderPlas remarked : “any time spent building and documenting software tools is time spent not writing research papers, which are the primary currency of the academic reward structure”.

Speaking personally, I learned a great deal about conducting research and scientific computing in my PhD; I could read and write code, squash bugs, and I wasn’t afraid of getting my hands dirty in monolithic code bases. As such, I felt comfortable at the command line but I failed to learn the basic tenets of proper code maintenance, unit testing, code review, version control, etc., that underpin good software engineering. While I had enough coding experience to have a sense of this at the time, I lacked the awareness of what I needed to know in order to improve or even where to start looking.

As is clear from the earlier statistic, this experience is likely not unique to me. It prompted me to share what I’ve learned since joining Invenia 18 months ago, so that it might guide those looking to make a similar move. The advice I provide is organised into three sections: the first recommends ways to learn a new programming language efficiently 1 ; the second describes some best practices you can adopt to improve the quality of the code you write; and the last commends the social aspect of community-driven software collaborations.

Lesson 1: Hone your craft

Practice : While clichéd, there is no avoiding the fact that it takes consistent practice over many many years to become masterful at anything, and programming is no exception.

Have personal projects : Practicing is easier said than done if your job doesn’t revolve around programming. A good way to get started either way is to undertake personal side-projects as a fun way to get to grips with a language, for instance via Project Euler , Kaggle Competitions , etc. These should be enough to get you off the ground and familiar with the syntax of the language.

Read code : Personal projects on their own are not enough to improve. If you really want to get better, you’ve got to read other people’s code: a lot of it. Check out the repositories of some of your favourite or most used packages—particularly if they are considered “high quality” 2 . See how the package is organised, how the documentation is written, and how the code is structured. Look at the open issues and pull requests. Who are the main contributors? Get a sense of what is being worked on and how the open-source community operates. This will give you an idea of the open issues facing the package and the language and the direction it is taking. It will also show you how to write idiomatic code , that is, in a way that is natural for that language.

Contribute : You should actually contribute to the code base you use. This is by far the most important advice for improving and I cannot overstate how instructive an experience this is. By getting your code reviewed you get prompt and informative feedback on what you’re doing wrong and how you can do better. It gives you the opportunity to try out what you’ve learned, learn something new, and improves your confidence in your ability. Contributing to open source and seeing your features being used is also rewarding, and that starts a positive feedback loop where you feel like contributing more. Further, when you start applying for jobs in industry people can see your work, and so know that you are good at what you do (I say this as a person who is now involved in reviewing these applications).

Study : Learning by experience is great but—at least for me—it takes a deliberate approach to formalise and cement new ideas. Read well-reviewed books on your language (appropriate for your level) and reinforce what you learn by tackling more complex tasks and venturing outside your comfort zone . Reading blog posts and articles about the language is also a great idea.

Ask for help: Sometimes a bug just stumps you, or you just don’t know how to implement a feature. In these circumstances, it’s quicker to reach out to experts who can help and maybe teach you something at the same time. More often than not, someone has had the same problem or they’re happy to point you in the right direction. I’m fortunate to work with Julia experts at Invenia, so when I have a problem they are always most helpful. But posting on public fora like Slack , Discourse , or StackOverflow is an option we all have.

Lesson 2: Software Engineering Practices

With respect to the environment and incentives in industry surrounding code maintainability, robustness, and testing, there are certain practices in place to encourage, enable, and ensure these qualities are met. These key practices can turn a collection of scripts into a fully implemented package one can use and rely upon with high confidence.

While there are without doubt many universities and courses that teach these practices to their students, I find they are often neglected by coding novices and academics alike, to their own disadvantage.

Take version control seriously: Git is a programming staple for version control, and while it is tempting to disregard it when working alone, without it you soon find yourself creating convoluted naming schemes for your files; frequently losing track of progress; and wasting time looking through email attachments for the older version of the code to replace the one you just messed up.

Git can be a little intimidating to get started, but once you are comfortable with the basic commands (fetch, add, commit, push, pull, merge) and a few others (checkout, rebase, reset) you will never look back. GitHub ’s utility, meanwhile, extends far beyond that of a programmatic hosting service; it provides documentation hosting , CI/CD pipelines , and many other features that enable efficient cross-party collaboration on an enterprise scale.

It cannot be overstated how truly indispensable Git and GitHub are when it comes to turning your code into functional packages, and the earlier you adopt these the better. It also helps to know how semantic versioning works, so you will know what it means to increment a package version from 1.2.3 to 1.3 and why.

Organise your code : In terms of packaging your code, get to know the typical package folder structure. Packages often contain src, docs, and test directories, as well as standard artefacts like a README, to explain what the package is about, and a list of dependencies, e.g. Project and Manifest files in Julia, or requirements.txt in Python. Implementing the familiar package structure keeps things organised and enables yourself and other users to navigate the contents more easily.

Practice code hygiene : This relates to the readability and maintainability of the code itself. It’s important to practice good hygiene if you want your code to be used, extended, and maintained by others. Bad code hygiene will turn off other contributors—and eventually yourself—leaving the package unused and unmaintained. Here are some tips for ensuring good hygiene:

• Take a design-first approach when creating your package. Think about the intended user(s) and what their requirements are—this may be others in your research group or your future self. Sometimes this can be difficult to know in advance but working iteratively is better than trying to capture all possible use cases at once.
• Think about how the API should work and how it integrates with other packages or applications. Are you building on something that already exists or is your package creating something entirely new?
• There should be a style guide for writing in the language, for example, BlueStyle in Julia and PEP 8 in Python. You should adhere to it so that your code follows the same standard as everyone else.
• Give your variables and functions meaningful, and memorable names. There is no advantage to obfuscating your code for the sake of brevity.
• Furthermore, read up on the language’s Design Patterns . These are the common approaches or techniques used in the language, which you will recognise from reading the code. These will help you write better, more idiomatic code.

Write good documentation : The greatest package ever written would never be used if nobody knew how it worked. At the very least your code should be commented and a README accompanying the package explaining to your users (and your future self) what it does and how to install and use it. You should also attach docstrings to all user-facing (aka public) functions to explain what they do, what inputs they take, what data types they return, etc. This also applies to some internal functions, to remind maintainers (including you) what they do and how they are used. Some minimum working examples of how to use the package features are also a welcome addition.

Lastly, documentation should evolve with the package; when the API changes or new use-cases get added these should be reflected in the latest documentation.

Write good tests : Researchers in computational fields might find familiar the practice of running “canonical experiments” or “reproducibility tests” that check if the code produces the correct result for some pipeline and is therefore “calibrated”. But these don’t necessarily provide good or meaningful test coverage . For instance, canonical experiments, by definition, test the software within the limits of its intended use. This will not reveal latent bugs that only manifest under certain conditions, e.g. when encountering corner cases.

To capture these you need to write adequate Unit and Integration Tests that cover all expected corner cases to be reasonably sure your code is doing what it should. Even then you can’t guarantee there isn’t a corner case you haven’t considered, but testing certainly helps.

If you do catch a bug it’s not enough to fix it and call it a day; you need to write a new test to replicate it and you will only have fixed the bug only when that new test passes. This new test prevents regressions in behaviour if the bug ever returns.

Lesson 3: Take Part in the Community

Undertaking a fraction of the points above would be more than enough to boost your ability to develop software. But the return on investment is compounded by taking part in the community forums on Slack and Discourse ; joining organizations on GitHub ; and attending Meetups and conferences . Taking part in a collaboration (and meeting your co-developers) fosters a strong sense of community that supports continual learning and encouragement to go and do great things. In smaller communities related to a particular tool or niche language, you may even become well-known such that your potential future employer (or some of their engineers) are already familiar with who you are before you apply.

Personal experience has taught me that the incentives in academic research can be qualitatively different from those in industry, despite the overlap they share. However, the practices that are instilled in one track don’t necessarily translate off-the-shelf to the other, and switching gears between these (often competing) frameworks can initially induce an all-too-familiar sense of imposter syndrome .

It’s important to remember that what you learn and internalise in a PhD is, in a sense, “selected for” according to the incentives of that environment, as outlined above. However, under the auspices of a supportive community and the proper guidelines, it’s possible to become more well-rounded in your skillset, as I have. And while I still have much more to learn, it’s encouraging to reflect on what I have learned during my time at Invenia and share it with others.

Although this post could not possibly relay everything there is to know about software engineering, my hope is that simply being exposed to the lexicon will serve as a springboard to further learning. To those looking down such a path, I say: you will make many many mistakes, as one always does at the outset of a new venture, but that’s all part of learning.

While these tips are language-agnostic, they would be particularly helpful for anyone interested in learning or improving with Julia .  ↩

Examples of high quality packages include the Requests in Python, and NamedDims.jl in Julia.  ↩

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Deprecating in julia 17 jun 2022, using meta-optimization for predicting solutions to optimal power flow 17 dec 2021, using neural networks for predicting solutions to optimal power flow 11 oct 2021.

• Programming

Top 10 Software Engineer Research Topics for 2024

Home Blog Programming Top 10 Software Engineer Research Topics for 2024

Software engineering, in general, is a dynamic and rapidly changing field that demands a thorough understanding of concepts related to programming, computer science, and mathematics. As software systems become more complicated in the future, software developers must stay updated on industry innovations and the latest trends. Working on software engineering research topics is an important part of staying relevant in the field of software engineering. 

Software engineers can do research to learn about new technologies, approaches, and strategies for developing and maintaining complex software systems. Software engineers can conduct research on a wide range of topics. Software engineering research is also vital for increasing the functionality, security, and dependability of software systems. Going for the Top Software Engineering Certification course contributes to the advancement of the field's state of the art and assures that software engineers can continue to build high-quality, effective software systems.

What are Software Engineer Research Topics?

Software engineer research topics are areas of exploration and study in the rapidly evolving field of software engineering. These research topics include various software development approaches, quality of software, testing of software, maintenance of software, security measures for software, machine learning models in software engineering, DevOps, and architecture of software. Each of these software engineer research topics has distinct problems and opportunities for software engineers to investigate and make major contributions to the field. In short, research topics for software engineering provide possibilities for software engineers to investigate new technologies, approaches, and strategies for developing and managing complex software systems. 

For example, research on agile software development could identify the benefits and drawbacks of using agile methodology, as well as develop new techniques for effectively implementing agile practices. Software testing research may explore new testing procedures and tools, as well as assess the efficacy of existing ones. Software quality research may investigate the elements that influence software quality and develop approaches for enhancing software system quality and minimizing the faults and errors. Software metrics are quantitative measures that are used to assess the quality, maintainability, and performance of software. 

The research papers on software engineering topics in this specific area could identify novel measures for evaluating software systems or techniques for using metrics to improve the quality of software. The practice of integrating code changes into a common repository and pushing code changes to production in small, periodic batches is known as continuous integration and deployment (CI/CD). This research could investigate the best practices for establishing CI/CD or developing tools and approaches for automating the entire CI/CD process.

List of Software Engineer Research Topics in 2024

Here is a list of Software Engineer research topics:

• Artificial Intelligence and Software Engineering
• Natural Language Processing 
• Applications of Data Mining in Software Engineering
• Data Modeling
• Verification and Validation
• Software Project Management
• Software Quality
• Software Models

Top 10 Software Engineer Research Topics

Let's discuss the top Software Engineer Research Topics in a detailed way:

1. Artificial Intelligence and Software Engineering

a. Intersections between AI and SE

The creation of AI-powered software engineering tools is one potential research area at the intersection of artificial intelligence (AI) and software engineering. These technologies use AI techniques that include machine learning, natural language processing, and computer vision to help software engineers with a variety of tasks throughout the software development lifecycle. An AI-powered code review tool, for example, may automatically discover potential flaws or security vulnerabilities in code, saving developers a lot of time and lowering the chance of human error. Similarly, an AI-powered testing tool might build test cases and analyze test results automatically to discover areas for improvement. 

Furthermore, AI-powered project management tools may aid in the planning and scheduling of projects, resource allocation, and risk management in the project. AI can also be utilized in software maintenance duties such as automatically discovering and correcting defects or providing code refactoring solutions. However, the development of such tools presents significant technical and ethical challenges, such as the necessity of large amounts of high-quality data, the risk of bias present in AI algorithms, and the possibility of AI replacing human jobs. Continuous study in this area is therefore required to ensure that AI-powered software engineering tools are successful, fair, and responsible.

b. Knowledge-based Software Engineering

Another study area that overlaps with AI and software engineering is knowledge-based software engineering (KBSE). KBSE entails creating software systems capable of reasoning about knowledge and applying that knowledge to enhance software development processes. The development of knowledge-based systems that can help software engineers in detecting and addressing complicated problems is one example of KBSE in action. To capture domain-specific knowledge, these systems use knowledge representation techniques such as ontologies, and reasoning algorithms such as logic programming or rule-based systems to derive new knowledge from already existing data. 

KBSE can be utilized in the context of AI and software engineering to create intelligent systems capable of learning from past experiences and applying that information to improvise future software development processes. A KBSE system, for example, may be used to generate code based on previous code samples or to recommend code snippets depending on the requirements of a project. Furthermore, KBSE systems could be used to improve the precision and efficiency of software testing and debugging by identifying and prioritizing bugs using knowledge-based techniques. As a result, continued research in this area is critical to ensuring that AI-powered software engineering tools are productive, fair, and responsible.

2. Natural Language Processing

a. Multimodality

Multimodality in Natural Language Processing (NLP) is one of the appealing research ideas for software engineering at the nexus of computer vision, speech recognition, and NLP. The ability of machines to comprehend and generate language from many modalities, such as text, speech, pictures, and video, is referred to as multimodal NLP. The goal of multimodal NLP is to develop systems that can learn from and interpret human communication across several modalities, allowing them to engage with humans in more organic and intuitive ways. 

The building of conversational agents or chatbots that can understand and create responses using several modalities is one example of multimodal NLP in action. These agents can analyze text input, voice input, and visual clues to provide more precise and relevant responses, allowing users to have a more natural and seamless conversational experience. Furthermore, multimodal NLP can be used to enhance language translation systems, allowing them to more accurately and effectively translate text, speech, and visual content.

b. Efficiency

The development of multimodal NLP systems must take efficiency into account. as multimodal NLP systems require significant computing power to process and integrate information from multiple modalities, optimizing their efficiency is critical to ensuring that they can operate in real-time and provide users with accurate and timely responses. Developing algorithms that can efficiently evaluate and integrate input from several modalities is one method for improving the efficiency of multimodal NLP systems. 

Overall, efficiency is a critical factor in the design of multimodal NLP systems. Researchers can increase the speed, precision, and scalability of these systems by inventing efficient algorithms, pre-processing approaches, and hardware architectures, allowing them to run successfully and offer real-time replies to consumers. Software Engineering training will help you level up your career and gear up to land you a job in the top product companies as a skilled Software Engineer. 

3. Applications of Data Mining in Software Engineering

a. Mining Software Engineering Data

The mining of software engineering data is one of the significant research paper topics for software engineering, involving the application of data mining techniques to extract insights from enormous datasets that are generated during software development processes. The purpose of mining software engineering data is to uncover patterns, trends, and various relationships that can inform software development practices, increase software product quality, and improve software development process efficiency. 

Mining software engineering data, despite its potential benefits, has various obstacles, including the quality of data, scalability, and privacy of data. Continuous research in this area is required to develop more effective data mining techniques and tools, as well as methods for ensuring data privacy and security, to address these challenges. By tackling these issues, mining software engineering data can continue to promote many positive aspects in software development practices and the overall quality of product.

b. Clustering and Text Mining

Clustering is a data mining approach that is used to group comparable items or data points based on their features or characteristics. Clustering can be used to detect patterns and correlations between different components of software, such as classes, methods, and modules, in the context of software engineering data. 

On the other hand, text mining is a method of data mining that is used to extract valuable information from unstructured text data such as software manuals, code comments, and bug reports. Text mining can be applied in the context of software engineering data to find patterns and trends in software development processes

4. Data Modeling

Data modeling is an important area of research paper topics in software engineering study, especially in the context of the design of databases and their management. It involves developing a conceptual model of the data that a system will need to store, organize, and manage, as well as establishing the relationships between various data pieces. One important goal of data modeling in software engineering research is to make sure that the database schema precisely matches the system's and its users' requirements. Working closely with stakeholders to understand their needs and identify the data items that are most essential to them is necessary.

5. Verification and Validation

Verification and validation are significant research project ideas for software engineering research because they help us to ensure that software systems are correctly built and suit the needs of their users. While most of the time, these terms are frequently used interchangeably, they refer to distinct stages of the software development process. The process of ensuring that a software system fits its specifications and needs is referred to as verification. This involves testing the system to confirm that it behaves as planned and satisfies the functional and performance specifications. In contrast, validation is the process of ensuring that a software system fulfils the needs of its users and stakeholders. 

This includes ensuring that the system serves its intended function and meets the requirements of its users. Verification and validation are key components of the software development process in software engineering research. Researchers can help to improve the functionality and dependability of software systems, minimize the chance of faults and mistakes, and ultimately develop better software products for their consumers by verifying that software systems are designed correctly and that they satisfy the needs of their users.

6. Software Project Management

Software project management is an important component of software engineering research because it comprises the planning, organization, and control of resources and activities to guarantee that software projects are finished on time, within budget, and to the needed quality standards. One of the key purposes of software project management in research is to guarantee that the project's stakeholders, such as users, clients, and sponsors, are satisfied with their needs. This includes defining the project's requirements, scope, and goals, as well as identifying potential risks and restrictions to the project's success.

7. Software Quality

The quality of a software product is defined as how well it fits in with its criteria, how well it performs its intended functions, and meets the needs of its consumers. It includes features such as dependability, usability, maintainability, effectiveness, and security, among others. Software quality is a prominent and essential research topic in software engineering. Researchers are working to provide methodologies, strategies, and tools for evaluating and improving software quality, as well as forecasting and preventing software faults and defects. Overall, software quality research is a large and interdisciplinary field that combines computer science, engineering, and statistics. Its mission is to increase the reliability, accessibility, and overall quality of software products and systems, thereby benefiting both software developers and end consumers.

8. Ontology

Ontology is a formal specification of a conception of a domain used in computer science to allow knowledge sharing and reuse. Ontology is a popular and essential area of study in the context of software engineering research. The construction of ontologies for specific domains or application areas could be a research topic in ontology for software engineering. For example, a researcher may create an ontology for the field of e-commerce to give common knowledge and terminology to software developers as well as stakeholders in that domain. The integration of several ontologies is another intriguing study topic in ontology for software engineering. As the number of ontologies generated for various domains and applications grows, there is an increasing need to integrate them in order to enable interoperability and reuse.

9. Software Models

In general, a software model acts as an abstract representation of a software system or its components. Software models can be used to help software developers, different stakeholders, and users communicate more effectively, as well as to properly evaluate, design, test, and maintain software systems. The development and evaluation of modeling languages and notations is one research example connected to software models. Researchers, for example, may evaluate the usefulness and efficiency of various modeling languages, such as UML or BPMN, for various software development activities or domains. 

Researchers could also look into using software models for software testing and verification. They may investigate how models might be used to produce test cases or to do model checking, a formal technique for ensuring the correctness of software systems. They may also examine the use of models for monitoring at runtime and software system adaptation.

The Software Development Life Cycle (SDLC) is a software engineering process for planning, designing, developing, testing, and deploying software systems. SDLC is an important research issue in software engineering since it is used to manage software projects and ensure the quality of the resultant software products by software developers and project managers. The development and evaluation of novel software development processes is one SDLC-related research topic. SDLC research also includes the creation and evaluation of different software project management tools and practices. 

Researchers may also check the implementation of SDLC in specific sectors or applications. They may, for example, investigate the use of SDLC in the development of systems that are more safety-critical, such as medical equipment or aviation systems, and develop new processes or tools to ensure the safety and reliability of these systems. They may also look into using SDLC to design software systems in new sectors like the Internet of Things or in blockchain technology.

Why is Software Engineering Required?

Software engineering is necessary because it gives a systematic way to developing, designing, and maintaining reliable, efficient, and scalable software. As software systems have become more complicated over time, software engineering has become a vital discipline to ensure that software is produced in a way that is fully compatible with end-user needs, reliable, and long-term maintainable.

When the cost of software development is considered, software engineering becomes even more important. Without a disciplined strategy, developing software can result in overinflated costs, delays, and a higher probability of errors that require costly adjustments later. Furthermore, software engineering can help reduce the long-term maintenance costs that occur by ensuring that software is designed to be easy to maintain and modify. This can save money in the long run by lowering the number of resources and time needed to make software changes as needed.

2. Scalability

Scalability is an essential factor in software development, especially for programs that have to manage enormous amounts of data or an increasing number of users. Software engineering provides a foundation for creating scalable software that can evolve over time. The capacity to deploy software to diverse contexts, such as cloud-based platforms or distributed systems, is another facet of scalability. Software engineering can assist in ensuring that software is built to be readily deployed and adjusted for various environments, resulting in increased flexibility and scalability.

3. Large Software

Developers can break down huge software systems into smaller, simpler parts using software engineering concepts, making the whole system easier to maintain. This can help to reduce the software's complexity and makes it easier to maintain the system over time. Furthermore, software engineering can aid in the development of large software systems in a modular fashion, with each module doing a specific function or set of functions. This makes it easier to push new features or functionality to the product without causing disruptions to the existing codebase.

4. Dynamic Nature

Developers can utilize software engineering techniques to create dynamic content that is modular and easily modifiable when user requirements change. This can enable adding new features or functionality to dynamic content easier without disturbing the existing codebase. Another factor to consider for dynamic content is security. Software engineering can assist in ensuring that dynamic content is generated in a secure manner that protects user data and information.

5. Better Quality Management

An organized method of quality management in software development is provided by software engineering. Developers may ensure that software is conceived, produced, and maintained in a way that fulfills quality requirements and provides value to users by adhering to software engineering principles. Requirement management is one component of quality management in software engineering. Testing and validation are another part of quality control in software engineering. Developers may verify that their software satisfies its requirements and is error-free by using an organized approach to testing.

In conclusion, the subject of software engineering provides a diverse set of research topics with the ability to progress the discipline while enhancing software development and maintenance procedures. This article has dived deep into various research topics in software engineering for masters and research topics for software engineering students such as software testing and validation, software security, artificial intelligence, Natural Language Processing, software project management, machine learning, Data Mining, etc. as research subjects. Software engineering researchers have an interesting chance to explore these and other research subjects and contribute to the development of creative solutions that can improve software quality, dependability, security, and scalability. 

Researchers may make important contributions to the area of software engineering and help tackle some of the most serious difficulties confronting software development and maintenance by staying updated with the latest research trends and technologies. As software grows more important in business and daily life, there is a greater demand for current research topics in software engineering into new software engineering processes and techniques. Software engineering researchers can assist in shaping the future of software creation and maintenance through their research, ensuring that software stays dependable, safe, reliable and efficient in an ever-changing technological context. KnowledgeHut’s top Programming certification course will help you leverage online programming courses from expert trainers.

Frequently Asked Questions (FAQs)

 To find a research topic in software engineering, you can review recent papers and conference proceedings, talk to different experts in the field, and evaluate your own interests and experience. You can use a combination of these approaches. 

You should study software development processes, various programming languages and their frameworks, software testing and quality assurance, software architecture, various design patterns that are currently being used, and software project management as a software engineering student. 

Empirical research, experimental research, surveys, case studies, and literature reviews are all types of research in software engineering. Each sort of study has advantages and disadvantages, and the research method chosen is determined by the research objective, resources, and available data. 

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Best Doctorates in Software Engineering: Top PhD Programs, Career Paths, and Salaries

The best PhDs in software engineering are a great tool for graduate students who want to earn advanced degrees, elevate their engineering skills, and access high-paying professions. With a software engineering PhD, you’ll be able to work in leadership positions in government, engineering, and education.

If you want to pursue doctoral studies and are looking for software engineering programs, look no further. In this article, we discuss the best software engineering jobs, listing PhD in software engineering salary ranges and prospective job growth projections in the software engineering field.

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What is a phd in software engineering.

A PhD in software engineering is an advanced study graduate degree in software engineering. It focuses on researching and implementing computer systems. Students are required to learn how to analyze the needs of their clients to design and deploy new software.

How to Get Into a Software Engineering PhD Program: Admission Requirements

To get into a software engineering PhD program, you need to complete an online application, pay the application fee, send your official transcripts, and provide GRE test scores. Other admission requirements may include letters of recommendation, a statement of purpose, and a current resume. The requirements will vary by institution.

PhD in Software Engineering Admission Requirements

• Online application and application fee
• Transcripts from each higher education institution attended
• Letters of recommendation
• Statement of purpose
• Current resume

Software Engineering PhD Acceptance Rates: How Hard Is It to Get Into a PhD Program in Software Engineering?

It is hard to get into a PhD program in software engineering because these programs are highly competitive. PhD programs require a high academic standing, extensive experience and educational background, and strong references. To accommodate the great amount of one-on-one time students need with professors, PhD class sizes are very small and have low acceptance rates.

How to Get Into the Best Universities

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Best PhDs in Software Engineering: In Brief

Best Universities for Software Engineering PhDs: Where to Get a PhD in Software Engineering

The best universities for software engineering provide high-quality education and prepare you to succeed in your future career.  If you’re wondering where to get a PhD in software engineering, check our list of the 10 best programs, below.

Auburn University (AU) was founded in 1856. It is a public land-grant research university, the second largest in the state of Alabama. AU offers a wide range of PhD programs in education, history, nutrition, and chemical engineering. 

PhD in Computer Science and Software Engineering

This 66-credit PhD program in computer science and software engineering guides PhD students as they develop research and build skills in cutting-edge disciplines. Throughout the program, they learn about advanced topics in algorithms, computer architecture, and operating systems. 

PhD in Computer Science and Software Engineering Overview

• Program Length: 4 years
• Acceptance Rate: Not stated
• Tuition and Fees: $560/credit (in state); $1,680/credit (out of statet)
• PhD Funding Opportunities: Graduate assistantships, Merriwether Fellowships, Presidential Graduate Research Fellowships, National Science Foundation Graduate Research Fellowships

PhD in Computer Science and Software Engineering Admission Requirements

• Bachelor's Degree or Master's Degree in Computer Science, Software Engineering, Cyber Security Engineering, or equivalent
• 3.0 GPA or above
• GRE score of at least 300, with a verbal score of at least 150, a quantitative score of at least 150, and a written score of at least 3
• TOEFL scores (for international students)

Carnegie Mellon University was founded in 1900. It is a private research university with over 6,000 graduate students enrolled across its seven colleges and independent schools. It offers programs in computer science, business, and electronics engineering. It boasts curious and passionate students who go on to build cutting-edge start-ups and innovative technology. 

PhD in Software Engineering

This degree in software engineering teaches students about computational methods, current policies, and societal and organizational needs. It aims to produce the next generation of software engineering professionals, educational leaders, and problem-solvers in the field.

PhD in Software Engineering Overview

• Program Length: 4-5 years
• Acceptance rate: Not stated
• Tuition: $23,200/semester 
• PhD Funding Opportunities: All applicants admitted to the doctoral program receive full financial support, but there are also many fellowship programs available, such as the Microsoft Research PhD Fellowship, the Siebel Scholars Program, and the Facebook Fellowship
• Online application
• Three letters of recommendation
• Unofficial transcript of all collegiate work completed post-high school

Clemson University is a public land-grant research university. It was founded in 1889 and currently consists of seven different colleges. More than 5,500 graduate students are enrolled across its graduate programs.

PhD in Computer Engineering

This PhD in computer engineering teaches students about computer hardware and architecture, programming systems, software engineering, and signals. Students are required to complete a total of 42 credits to complete this program. Students in the program have the opportunity to work at the SCE&G Energy Innovation Center, an advanced energy systems testing facility. 

PhD in Computer Engineering Overview

• Program Length: 2 years 
• Tuition: $5,056/semester (in-state)/ $10,644/semester (out of state)
• PhD Funding Opportunities: Graduate assistantships, Microsoft Research PhD Fellowship, NVIDIA Fellowship, Google PhD Fellowship

PhD in Computer Engineering Admission Requirements

• Online application and $80 application fee
• Unofficial transcripts from each institution attended

Cornell University is a private Ivy League land-grant research university. It was founded in 1865 with the intention to offer high-quality education and contribute in all fields of knowledge. It currently has over 8,800 graduate students enrolled.

PhD in Electrical and Computer Engineering

Cornell’s PhD program in electrical and computer engineering prepares students for a successful career in research, teaching, and development across all industries. Graduate students are required to engage in cutting-edge coursework and conduct studies in the field.

PhD in Electrical and Computer Engineering Overview

• Program Length: Not stated
• Tuition: $29,500/year
• PhD Funding Opportunities: Graduate assistantships (research and teaching) and fellowships

PhD in Electrical and Computer Engineering Admission Requirements

• GPA of 3.5 or above
• Academic statement of purpose
• Personal statement
• Unofficial transcript from each university attended
• Resume 

Massachusetts Institute of Technology (MIT) was established in 1861. It is a private land-grant research university with over 6,800 enrolled graduate students. It offers PhD programs in the humanities, social sciences, and STEM fields.

PhD in Computational Science and Engineering

This PhD program requires students to specialize in a computation-related field of their choice. Courses are taught across different departments, including mathematics, mechanical engineering, and materials science and engineering. Graduate students in this program are required to complete 60 credits of coursework and thesis preparation. 

PhD in Computational Science and Engineering Overview

• Tuition: $28,795/semester
• PhD Funding Opportunities: Graduate assistantships

PhD in Computational Science and Engineering Admission Requirements

• Minimum of a bachelor’s degree or its equivalent
• Transcripts from all institutions attended
• Statement of objectives

Purdue University is a public research university. It was founded in 1869 and is now the flagship campus of the Purdue University system. It offers over 70 master's and doctorate programs and has more than 10,000 graduate students enrolled.

This PhD in Computer Engineering prepares graduate students to take on real-world problems in big data, cloud computing, the Internet of Things (IoT), and machine learning. This program’s graduates work in industrial research, development, and academia. During their studies, PhD students have access to well-funded research assistantships. 

• Program Length: 4-5 years (6-year limit)
• Tuition: $4,859/semester (in state); $9,401/semester (out of state)
• PhD Funding Opportunities: Graduate assistantships, fellowships
• Master’s degree with a minimum GPA of 3.25
• Transcript from every institution of higher education attended
• Statement of Purpose
• GRE scores (optional)

University of California, Irvine , is a public research university. It was established in the 1960s and is one of the 10 campuses of the University of California System. It has 14 schools, several interdisciplinary programs, and over 6,600 graduate students.

The 48-credit degree program in software engineering teaches students how to design new tools, engage in relevant research in the software industry, create infrastructures, and develop theories about software and its utility.

• Program Length: 6 years
• Tuition: $3,814.00/semester
• PhD Funding Opportunities: Teaching assistantships, reader fellowships, Steckler Family Endowed Fellowship, Google PhD Fellowship 
• Bachelor’s degree with a minimum cumulative undergraduate GPA of 3.0
• English proficiency tests (all applicants)
• Transcripts for all institutions attended since high school

University of Miami (UM) was founded in 1925. It is a private research university with 12 colleges and schools. UM offers 67 doctoral degree programs and has over 6,400 graduate students. 

Graduate students in this PhD program learn about programming languages and algorithms, computer networks, architecture, and digital systems. They must complete 30 credits, pass their qualifying examination, and defend their dissertation to complete the program.

• Tuition: $19,530/semester
• PhD Funding Opportunities: Internal and external fellowships, scholarships
• Transcripts from each post-secondary institution attended
• Official GRE scores with a minimum score of 310

University of Michigan is a public research university that consists of 19 colleges. It was founded in 1817, offers 100 doctoral programs, and has over 16,000 graduate students enrolled. The school offers over 3,000 courses and is ranked third among the leading public universities in the US. 

PhD in Computer Science and Engineering

This PhD program teaches advanced topics in computer science and engineering. The degree supports students in conducting research and writing publishable papers. This program is intended for those who wish to pursue a career in academics, and PhD students are expected to contribute to the field of computer science and engineering through their research. 

PhD in Computer Science and Engineering Overview

• Program Length: 4- 5 years
• Tuition (and Fees): $1,730/credit (resident); $3,132/credit (non-resident)

PhD in Computer Science and Engineering Admission Requirements

• Research interest
• Faculty interest
• Official transcripts from each bachelor’s, master’s, professional, and doctoral degree earned

University of Utah was established in 1850. It is a public research university, and the flagship institution of the Utah System of Higher Education. It offers several programs in biology, computer science, and political science. Its 8,000 graduate students can choose from over 200 degree programs and access $641,000,000 in research funding.

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This PhD program in computer engineering prepares students for a successful career in the software engineering industry, academia, and government. It teaches advanced topics in computer engineering, such as digital communication and advanced embedded software. Students will conduct research, pass qualifying examinations, and defend a dissertation. 

• Program Length: 3 years
• Tuition and Fees: $1,271.79/credit (in state); $4,517.11/credit (out of state)
• PhD Funding Opportunities: Teaching assistantships, ASEE SMART Fellowships, National Science Foundation (NSF) – Graduate Resources, Microsoft Research PhD Fellowship Program
• Master of science degree 
• Personal Statement

Can You Get a PhD in Software Engineering Online?

Yes, you can get a PhD in Software Engineering. However, there are very few software engineering PhD programs available online, as most degree programs at this level require hands-on involvement. It would be easier to find PhD programs in computer science, which will cover aspects of engineering. If you want to earn your PhD in Software Engineering, you’ll more than likely need to be willing to attend an in-person program.

How Long Does It Take to Get a PhD in Software Engineering?

It takes four to five years to get a PhD in software engineering. This is the average duration for most PhD programs. Throughout the program, you will complete coursework, sit for qualification exams, and write and defend your final doctoral dissertation.

The first year usually covers core courses. The second and third years are for advanced courses related to the specialization. During the fourth and fifth years, students research and defend their PhD dissertations.

Is a PhD in Software Engineering Hard?

Yes, a PhD in Software Engineering is hard. PhD programs are hard to complete because they’re meant to develop future experts, are highly specialized, and require a lot of independent work. Over the course of five years, students are expected to learn advanced topics in their field, develop cutting-edge, relevant research, write and publish papers, and write final dissertations that dissect original research.

How Much Does It Cost to Get a PhD in Software Engineering?

On average, it costs $19,314 a year to get a PhD in software engineering, according to the National Center for Education Statistics. This value may vary. University prestige, public or private university status, and student resident status are some aspects that affect tuition.

How to Pay for a PhD in Software Engineering: PhD Funding Options

PhD funding options that students can use to pay for a PhD in Software Engineering include research and teaching assistantships, internal and external fellowships, and scholarships. Many universities have internal funding for PhD students, which you can access through the institution’s financial office.

Best Online Master’s Degrees

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What Is the Difference Between a Software Engineering Master’s Degree and PhD?

The main difference between a software engineering master’s degree and a PhD is that master’s degrees are focused on preparing students for the job market, while a PhD program is more research-based.

Software engineering PhDs prepare students for advanced careers in research and academia. Master’s degrees are a lower qualification but are often more job-focused. Other differences between these types of graduate programs include career options and the time it takes to complete.

Master’s vs PhD in Software Engineering Job Outlook

The job outlook for master’s and PhD graduates in software engineering are similar since both qualifications make you eligible for similar positions. Even though their salaries are different, both professionals are looking at the same job outlook.

Postsecondary teaching employment, a common professional for PhD-holders, is expected to grow by 12 percent in the next decade.  Meanwhile, employment in web development, a position better fitted for a Master’s Degree in Software Engineering, is expected to grow by 13 percent over the next decade, according to the US Bureau of Labor Statistics.

Difference in Salary for Software Engineering Master’s vs PhD

While master’s and doctorate students share many of the same job positions, their salaries vary slightly. When applying for the same position, a PhD graduate can bargain for a higher salary with their advanced knowledge and skills. However on average, according to PayScale, a software engineer with a master’s degree earns, on average, $111,000 per year, while a software engineer with a PhD in the field earns $103,000 , annually.

Related Software Engineering Degrees

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Why You Should Get a PhD in Software Engineering

You should get a PhD in software engineering because the demand for software engineers is high, meaning the salaries are high as well. You can complete a PhD program with full funding, and the program will elevate your career, improve your communication skills, and hone career-specific skills. It also qualifies you for senior positions and to teach at the university level.

Reasons for Getting a PhD in Software Engineering

• Higher salaries. Professionals with a software engineering PhD generally earn more than those who have bachelor’s or master’s degrees.
• Funding opportunities. Most students pursuing a PhD in software engineering are eligible for research and teaching assistantships, internal and external fellowships, and scholarships that cover their full tuition.
• Improve communication skills. Software engineering PhD students are required to research and write papers. They are then required to dissect their findings in conferences and seminars, which builds communication skills.
• Hone career-specific skills. Throughout a software engineering PhD program, students work on their programming, software development, software testing and debugging problem-solving, teamwork, and other career-specific skills.

Getting a PhD in Software Engineering: Software Engineering PhD Coursework

Besides research and writing a dissertation, getting a PhD in software engineering requires completing courses in software engineering research, symbolic mathematical modeling and analysis, and human-focused empirical research. Software engineering PhD coursework also includes topics like design and engineering of software systems and the applications of software in society, business, and policy.

Software Engineering Research

A software in engineering research course is designed to prepare students to develop relevant research skills. It introduces field research strategies, discusses developments that led to current inquiries, and allows students to critique and evaluate research papers.

Symbolic Mathematical Modeling and Analysis

In this course, students engage in research methods that include discrete models, proofs, and software-relevant mathematical topics. The most common areas of study in this course are machine learning, programming language semantics, and formal logic.

Human-focused Empirical Research

This course focuses on behavioral science research methods. It touches on human-based topics relevant to software engineering and includes the study of interviews, case studies, surveys, human subjects experiments, and mining software repositories.

Design and Engineering of Software Systems

The design and engineering of software systems course requires a significant engagement with software design, consideration of software artifacts, and exposure to tradeoffs at the core of software engineering.

Software in Society, Business, and Policy

This course covers ways in which software interacts with problems in society, businesses, and public policy. It focuses on topics like the social web, information security and privacy, privacy engineering, and the foundations of privacy.

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How to Get a PhD in Software Engineering: Doctoral Program Requirements

To get a PhD in software engineering, you need to meet your school’s program requirements. These include completing the required coursework, passing the qualifying and candidacy exams, creating a program of study, and defending a final dissertation.

A PhD in software engineering requires the completion of a few core courses in the first year of the program. Once you are done with these courses, you’ll need to be evaluated to continue the program.

At the end of the first year of the software engineering PhD program, students have to pass a qualifying exam. This examination evaluates students on their knowledge in core subjects that they studied throughout the year.

In the second year of study, students enroll in more specialized courses. With the help of an advisor, students create a program of study for the rest of the program, including finding a permanent advisor to guide them through their dissertation.

Once you’re done with the advanced courses, the faculty will have to assess your knowledge in the different areas of your specialization. Students also have to present a preliminary sample of what their dissertation will be. After passing this exam, students are considered PhD candidates.

At the end of the software engineering PhD program, students must present and defend their final dissertation in an oral presentation. Once they pass their presentation, they must deliver a copy of their final work.

Potential Careers With a Software Engineering Degree

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PhD in Software Engineering Salary and Job Outlook

Getting a PhD in software engineering will give you access to jobs that pay well above the national average and grant you career stability. Career prospects are positive since employment in the field is projected to grow over the next decade.

What Can You Do With a PhD in Software Engineering?

With a PhD in software engineering, you can get a job as a computer and information systems manager, a computer and information research scientist, or a senior software developer. You might also become a database administrator, database architect, or computer science postsecondary teacher. With a PhD, you can access senior roles in the industry.

Best Jobs with a PhD in Software Engineering

• Computer and Information Systems Manager
• Computer and Information Research Scientist
• Software Developer
• Database Administrator and Architect
• Computer Science Postsecondary Teacher

What Is the Average Salary for a PhD in Software Engineering?

The average salary for a PhD in software engineering is $103,000 per year, on average, according to PayScale. This salary average varies with the career path you choose, the industry you’re working in, and the state you’re based in.

Highest-Paying Software Engineering Jobs for PhD Grads

Best Software Engineering Jobs with a Doctorate

Throughout the following sections, we’ll discuss some examples of the best software engineering jobs with a doctorate. We’ll also cover how much they pay, the job outlook, and the highest-paying states for each job.

Computer and information systems managers plan, coordinate, and direct every computer-related activity in their company. They are responsible for making sure the company’s current computer systems can support business goals. 

This position carries a lot of responsibility and can be specialized depending on the specific company needs and your skillset. Your title may be chief information officer, chief technology officer, IT director, or IT security manager.

• Salary with a Software Engineering PhD: $162,930
• Job Outlook: 11% job growth from 2020 to 2030
• Number of Jobs: 482,000
• Highest-Paying States: New York, California, and New Jersey

Computer and information research scientists create computer software and hardware and improve the existing tech. They work across industries and their main responsibility involves studying and solving problems in computing. 

• Salary with a Software Engineering PhD: $142,650
• Job Outlook: 22% job growth from 2020 to 2030
• Number of Jobs: 33,000
• Highest-Paying States: Oregon, Arizona, and Texas

Software developers create computer applications to help organizations reach their full potential. They oversee the entire development process, from communicating with clients to coding the program, to launching the new software and performing software maintenance.

• Salary with a Software Engineering PhD: $120,990
• Number of Jobs: 1,847,900
• Highest-Paying States: California, Washington, and Maryland

Database administrators and architects create and organize software systems to store and secure information. They evaluate their organization’s software requirements, design database models, code new data architecture, and check for errors and inefficiencies.

• Salary with a Software Engineering PhD: $96,110
• Job Outlook: 8% job growth from 2020 to 2030
• Number of Jobs: 168,000
• Highest-Paying States: New Jersey, Washington, and California

Postsecondary computer science professors teach advanced courses in computer sciences. They may specialize in a field of computer science like software engineering. Usually, they work in the computer science department of a university and teach one or two courses a semester.

• Salary with a Software Engineering PhD: $89,610
• Job Outlook: 12% job growth from 2020 to 2030
• Number of Jobs: 37,800
• Highest-Paying States: California, Oregon, and District of Columbia

Is a PhD in Software Engineering Worth It?

Yes, getting a PhD in software engineering is worth it. With a PhD, you will develop relevant skills for the job market, work on your research and communication skills, and get a high-paying job in the field. A software engineering PhD opens doors for a range of high-paying positions. While most PhD graduates want to pursue a career in academics, you can also choose to work for the government or engineering companies.

Additional Reading About Software Engineering

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PhD in Software Engineering FAQ

Yes, there are several software engineering events that you can attend for learning and networking. This October, the DotNETOS Conference will take place online, covering .NET 5, .NET 6, and .NET Core for people invested in the .NET community. You can attend for free.

The difference between a software engineer and a programmer is in their focus. Programmers create functional code while software engineers design software from an engineering perspective. Software engineers have to consider end-users and are also programmers themselves.

Some of the best software engineer tools include Adobe Dreamweaver, Gnu Debugger, and Notepad++. A few other popular tools for software engineers are GitHub, Stack Overflow, and Visual Studio.

The top skills for software engineers include programming languages, programming skills, cloud computing foundations, knowledge of DevOps practices, familiarity with the software development process, and strong communication skills.

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Doctoral / PHD Programs in Software Engineering

26 universities offer graduate PHD program in Software Engineering

Northwestern University

The PhD emphasizes excellence in education and research, providing a foundation for careers in industry, academia, and research.

The PhD program in computer engineering prepares students to become innovative leaders in academic, industrial, and entrepreneurial settings. This allows students to focus on their research.

PhD candidates may elect to participate in the Crown Family Graduate Internship Program.

The PhD program in computer engineering emphasizes excellence in education and research, providing graduates with a solid foundation for a career in industry, academia, and research labs.

In the last decade, recent graduates have founded than half a dozen successful start-ups.

Request a customized program guide PhD in computer engineering.

Electrical and Computer Engineering

• GRE Required:  Yes
• Research Assistantships:  965
• Teaching Assistantships:  1095
• Financial Aid: Register to view the details

Columbia University in the City of New York

Combining key aspects of electrical engineering and computer science.

Students learn the fundamentals of circuits, systems, and software associated with the design of programmable systems as used for general purpose computing, communications, control, or signal processing. Because of their broad skills in both hardware and software, students in computer engineering are in high demand for employment after graduation. Computer engineering students are also positioned to pursue graduate programs in either computer science or electrical engineering.

We do not currently offer a PhD and suggest PhD candidates Computer Science or Electrical Engineering department.

Computer Engineering

• Research Assistantships:  1081
• Teaching Assistantships:  1757

Carnegie Mellon University

Software is becoming ever important to our daily lives, as well as every sector of industry. But as software systems increase in capability, they increase in complexity, resulting in delays, defects, and vulnerabilities.

Our Ph.D. program in Software Engineering seeks to educate the next generation of high-impact software engineering research, development, and educational leaders who will solve the problems associated with building large-scale and critical software systems.

Applications to the Ph.D. program in Software Engineering are accepted every year with a deadline in December. The next deadline is December 12, 2022, 3 pm EST (!).

Software and Societal Systems Department

• Research Assistantships:  3032
• Teaching Assistantships:  -

231 universities offer the Master's program in Software Engineering.

Which one best suits your need?

University of Virginia-Main Campus

May 22 BME Final Exercises 2022 Diploma Ceremony.

Computer Engineering alumni who have Completed a Ph.D. since the graduate program was approved in 2004.

Computer Engineering Program Ph.D. Graduates

• GRE Required:  Register to view the details
• Research Assistantships:  Register to view the details
• Teaching Assistantships:  Register to view the details

University of Wisconsin-Madison

Ranked 6th in the national research category for public universities by the National Science Foundation, UW-Madison continues to be a leader of exploration and discovery.

Carolyn Schaefer, a PhD student in engineering physics, works on the Pegasus-III fusion experiment.

Boston University

External collaborations with industry and government laboratories are encouraged. As a student in Boston, you will be in the midst of a vibrant high-tech research community where external collaborations with industry, government, and other universities are common. Your experience will likely not be limited to Boston PhD students are supported by the department to present their work at many key conferences around the world. Our graduates go on to conduct independent basic or applied research, with careers in academia, industry, and government.

Demonstration of a strong foundation in computer engineering as measured by the successful completion of coursework and the qualifying examination.

Making an original and substantial contribution to the discipline of computer engineering as measured by conference presentations, conference publications, or peer-reviewed journal articles, and the completion of a successful PhD thesis.

Demonstrating the ability to effectively communicate original scientific research in computer engineering as measured by the successful oral defense of a prospectus, PhD thesis, conference presentations, conference publications, or peer-reviewed journal articles.

Or higher are accepted for fulfilling PhD credit requirements. In non-structured (P F) courses, the P grade is acceptable for fulfilling PhD requirements. PhD students who receive grades of C+ or lower in 3 courses will be withdrawn from the program.

Post-BS PhD students (64 credits): Minimum eight courses, of which four need to be EC 500 and 700-level courses.

Post-MS PhD students (32 credits): Minimum two EC 500 and 700-level courses.

PhD Candidacy: PhD students must show technical (TPC) and research (RPC) proficiency in order to achieve PhD candidacy.

Post-BS PhD students: GPA 3.7 in four ECE courses within the first three academic semesters.

Post-MS PhD students: GPA 3.7 in two ECE courses within the first two academic semesters.

Research Proficiency Criterion (RPC): The research proficiency requires a student to pass an oral examination related to a research article (chosen by the student and approved by the ECE Graduate Committee) and its background material. If a student fails the oral examination on the first attempt, they are given a makeup oral examination. All PhD students are required to satisfy the RPC by the end of the first year in the PhD program. Unless a student passes the oral examination on either the first or the second attempt, the student will not be allowed to stay in the PhD program.

Dissertation Defense: The student defends their dissertation, which must consist of novel work in the area of computer engineering. The dissertation should be defended within five years of candidacy.

Note that this information may change at any time. Read the full terms of use.

University of Virginia School of Engineering and Applied Science

Northeastern university.

Northeastern offers a PhD in Computer Engineering (PhDCE) that is completely research based with minimal and flexible course requirements which can be pursued as full-time or part-time. As a computer engineering student at Northeastern you will study computer architecture, software engineering, computer-aided design (VLSI), microprocessor-based design, and applied algorithms.

In addition to a broad background in mathematics, physics, and chemistry, this curriculum gives you solid foundation in both hardware and software design. RISC microprocessors, object-oriented Java and cellular networks are just three of the technologies you will encounter in the program.

In the past ten years the internet has revolutionized all aspects of our lives, from the way we communicate to the way we do business. Wireless communication, online commerce, medicine, and multimedia are examples of new applications that have transformed our world. Computer engineers developed the fundamental technologies that made the web possible, including high performance microprocessors, gigabit networks and object-oriented computer languages. Demand for computer engineers has increased dramatically in recent years. Students with a strong background in computer engineering are aggressively recruited by cutting edge computer companies nationwide.

The ECE department offers a variety of graduate courses giving students flexibility of planning their course requirements according to their research requirements and personal interests. Many of graduate courses are offered in two sections in-class and streaming video. Part-time students and full-time students who have schedule conflicts can register in the streaming video sections.

Can be combined with a Gordon Engineering Leadership certificate.

The ability to use basic engineering concepts flexibly in a variety of contexts.

With the large number of high-tech firms in and around Boston, both start-ups and large multinational corporations, many PhD students do an internship during their program while remaining right here in Boston. Internships can be informally arranged for several months at any time during the calendar year, and PhD students can also take advantage of the formally arranged co-op program which entails 6 months of work experience preceded by several professional development courses to prepare students.

Our graduates pursue careers within academia and beyond.

Case Western Reserve University

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Chemical and Biomolecular EngineeringToggle Chemical and Biomolecular Engineering.

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Leadership Excel and Achievement Program (LEAP), Graduate Certificate.

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Institute for Integration of Management and Engineering (IIME).

Degree: Doctor of Philosophy (PhD)Field of Study: Computer Engineering.

Requirements for admission include a strong record of scholarship in a completed bachelor degree program in a field of engineering, mathematical or physical sciences, and fluency in written and spoken English. The University requires all foreign applicants to show English proficiency by achieving a TOEFL score of at least 577 on the paper-based exam or 90 on the internet-based exam. Submission of GRE scores for graduate applications is NOT required. Such provisional students may be advanced to full standing upon completion of prerequisite conditions stipulated in the letter of admission.

Course registration is performed through the Student Information System (SIS). Each semester before registration, students should update any personal information that may have changed by logging into SIS and editing the appropriate information. All registration holds must be lifted in order to successfully complete the registration process.

Upon passing the qualifier, full-time PhD students will be required to assemble the dissertation guidance committee, prepare a dissertation proposal, and present this proposal to the committee for their approval. This process should be completed within one semester of passing the PhD qualifier.

In order to successfully complete the PhD Degree Program, a student must satisfy the following requirements:.

Have an approved Program of Study and complete the CWRU courses in the approved Program of Study with a cumulative grade point average of 3.25 or greater.

The final consideration of whether to admit the student to PhD candidacy will be taken by the student dissertation guidance committee after the student has passed the PhD Qualifier.

After passing the Qualifier and being admitted to PhD candidacy, the PhD candidate is required to pass a Dissertation Proposal Exam on a timely basis, generally within one semester after being admitted to candidacy. This exam shall be administered by the student dissertation guidance committee and consists of a written dissertation proposal and an oral presentation of the proposed dissertation research. As part of the oral presentation, the student will be expected to answer questions covering the proposed research as well as questions on related topics as deemed appropriate by the student dissertation guidance committee. The written dissertation proposal must be received by the committee members at least ten days before the date scheduled for the oral exam and presentation. The Dissertation Proposal Exam, the PhD research, the final oral dissertation defense, and all other requirements in the student PhD program of study must be completed within five years after the student is admitted to PhD candidacy.

All PhD students shall fulfill the PhD residency requirements set forth by the Case School of Engineering and the School of Graduate Studies. Specifically, the PhD student is required either to register for at least 9 credit hours during each of two consecutive semesters or to engage in academic work (taking courses, assisting in course development and or teaching, fully engaging in research, or some other scholarly activities) in at least six consecutive terms (fall, spring, or summer) between matriculation and a period not exceeding 5 years after the first credited hour of ECSE 701. The period during a leave of absence cannot be counted to fulfill the residency requirement.

For PhD policies and procedures, please review the School of Graduate Studies section of the General Bulletin.

At least 18 credit hours of coursework must be taken at CWRU. In addition, the student is also required to complete a minimum of 18 credit hours of ECSE 701 to fulfill the requirement for PhD-level research. Acceptable courses include suitable CWRU courses at the 400-level or higher and approved graduate-level courses taken at other institutions. Students holding an MS degree in an appropriate field of study from CWRU or another degree-granting institution may apply up to 18 credit hours of coursework completed for their MS degree towards the aforementioned 36 credit hour requirement.

Each PhD student is required to have a fully-approved Academic Program before taking the PhD Qualifying examination and before registering for the final 18 credit hours of the program.

A minimum of two courses in mathematics, statistics, or basic science.

At least six approved courses from the student major area of study. At least 4 of these courses must be from within the ECSE department.

Four additional courses that are not listed under the student major program area. These courses should satisfy the requirement for breadth in the student program of study.

A minimum of 18 credit hours of PhD Dissertation research as noted by enrollment in and successful completion of ECSE 701.

The total number of 3 credit hour courses in the Academic Program is at least 12 credit hours beyond the BS level.

The PhD program includes a colloquium and public presentation requirement.

All PhD students are required to register for and pass ECSE 500 for a total of three semesters of the PhD Program, and this is expected before Advancement to Candidacy. This is a 0 credit hour required course. Students, such as part-time students working in industry, may propose an alternative arrangement for fulfilling this requirement, by submitting a written petition to the Graduate Studies Committee.

All PhD students must give a public presentation of their research, in addition to their PhD dissertation defense. This presentation must be given either at a research conference, in the ECSE seminar series, workshop presentations or similar presentations in a public venue. MS thesis and PhD dissertation defenses cannot be used to fulfill the public presentation requirement.

A student shall be admitted to PhD candidacy only after they have passed the PhD Qualifying Examination. The Qualifying Exam is intended to test the students' knowledge in the student chosen major program area of Computer Engineering. The objectives of the exam are:.

To assess the PhD student understanding of the fundamental concepts in Computer Engineering as embodied in the respective graduate curriculum.

To ensure that the student have the ability to pursue PhD level research, and have mastered the graduate level coursework necessary to succeed as researchers.

Full-time PhD students are recommended to take the PhD qualifier before the beginning of their third semester of full-time (or equivalent) enrollment, and must pass the exam within two years of being admitted to the program. For part-time students, the Qualifying Exam must be passed before than 27 credit hours of coursework have been completed. For students who must take remedial courses to make up for shortcomings in their engineering and mathematics knowledge base, the deadline can be extended to the fifth semester of full-time (or equivalent) enrollment, but this requires a petition to the ECSE Graduate Committee. Students have two opportunities to pass the PhD Qualifier. A student who fails to pass the Qualifier after two attempts will not be allowed to continue in the PhD program in the Electrical, Computer, and Systems Engineering.

To pass the PhD Qualifier, the student must demonstrate proficiency in two parts:.

The written part of the Qualifying Exam for Computer Engineering will be offered at least once a year at the end of the spring semester.

Part 2 will consist of an oral exam based on the areas of the written examination. However, the oral exam may be waived if the student has performed well in all three topic areas of the written exam.

Computer Engineering, PhD Case Western Reserve University

University of connecticut.

The general exams will be given twice per year (January and May), in general, during the same week as the Systems general exams.

Written Exams will be required on 4 courses (PhD and MS-Plan B). General Exams may not be taken on independent study courses.

Students will have to take the exams either all at the same time or in blocks of two courses at a time.

Corresponding courses in which the subject matter is tested are also listed. Both Ph.D. and M.S. Plan B students are required to pass this section.

University of Massachusetts-Amherst

Computer engineers develop designs based on computer hardware and complex digital logic devices, aimed for use in computation, communication, entertainment, information processing, and artificial intelligence. Career fields for computer engineers include computer-aided manufacturing, hardware design, software design, and integrated circuit design.

The Electrical and Computer Engineering (ECE) Department at the University of Massachusetts Amherst offers both MS and PhD degrees.

4+1 Accelerated Master Degree in Electrical and Computer Engineering.

Master of Science in Electrical and Computer Engineering.

You'll be prepared for a career in computer engineering and allied professions or for further study at a graduate or professional school.

The purpose of the Distinguished Staff Award is to recognize the crucial role played by staff members in facilitating the success of UMass graduate students.

What kind of scholarships are available for Graduate Programs in Software Engineering?

We have 155 scholarships awarding up to $1,270,915 for Masters program in for Software Engineering, targeting diverse candidates and not restricted to state or school-based programs.

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Program overview

The PhD in Software Engineering program leads to the highest degree offered by the Faculty and is designed to provide students an opportunity to obtain the greatest possible expertise in their chosen field through intensive research. Advancement of analytical and/or experimental knowledge through a combination of specialized courses and a research thesis under the supervision of an experienced researcher forms the main component of the doctoral program. Where possible, research of interest to industry is encouraged.

The objective of the PhD in Software Engineering program is to educate highly qualified researchers required for the expansion of fundamental knowledge and technological innovation through research and development, as well as the needs of institutions of higher learning.

Program details

Admission requirements, admission requirements.

Admission on a full-time basis

• Master’s degree or equivalent with high standing in engineering or computer science, or in a cognate discipline.
• Holders of a bachelor’s degree will, in general, be considered for admission to a master’s program only. After completion of a minimum of one term of full-time study in the Master's degree, they may, upon application, be recommended by the Department and approved by the GCS Associate Dean of Research and Graduate Studies for admission to a PhD program.

Admission on a part-time basis

• Master’s degree with high standing in engineering, computer science or a cognate discipline.

Proficiency in English

Proficiency in English. Applicants whose primary language is not English must demonstrate that their knowledge of English is sufficient to pursue graduate studies in their chosen field. Please refer to the English language proficiency page for further information on requirements and exemptions .

Degree requirements

(90 credits), doctor of/doctorate in philosophy (phd).

Application process

Please apply  online . Read the  how-to guide  for application procedures. 

1. Submit your application and pay a $100 CAD application fee. A student ID number will be issued

2.  Upload your documents online . You can also upload your documents by logging in to the Student Hub and going to  My CU Account . 

3. A completed file that is ready to be assessed will include:

• Application form and Fee
• Curriculum Vitae (CV)
• Three Letters of Reference and assessment form
• Statement of purpose
• Transcripts  (with mark sheets if applicable) for all post-secondary institutions attended
• Proof of Canadian citizenship  (if applicable)
• Applicants whose primary language is not English, are required to submit  official language test scores , unless exempted.

4. An admission offer will not be issued until a supervisor match has been made. Students are encouraged to review the list of faculty members' field of interests  and directly contact those with whom you would like to work.  

For initial assessment purposes, scanned and uploaded copies of documents are accepted.  To finalize a file, once admitted, Concordia University will require official documents.

Application deadlines

Core and advanced courses that are typically offered include:

• Software engineering development process
• Mining large software system data
• Software re-engineering
• Software comprehension and maintenance
• Software architecture and design
• Software requirements, verification, testing and validation
• Human computer interface design
• Software project management
• Services computing: Foundations, design and implementations

Students generally receive bursary funding for each of the first three years of doctoral studies which could cover their living expenses. International students, who pay higher fees, may receive more funding.

Please consult the  School of Graduate Studies  to keep up-to-date with all funding initiatives from internal (Concordia University and its donors) and external (government and industry) sources as well as Financial Aid and Awards .

Faculty research and industrial partnerships

Faculty members have a wide range of collaboration with universities as well as industry partners (e.g., Defence R&D Canada, Ericsson, Marinvent, Opal-RT).  Learn  about this research synergy taking place in research groups . 

The department is housed in a custom-designed facility equipped with state-of the-art laboratories and research centres, including:

• Centre for Pattern Recognition and Machine Intelligence (CENPARMI) 
• ENCS Software Engineering Research Center (SERC)
• ENCS Data Science Research Centre (DSRC)

Your professional future

This program prepares graduates for faculty positions in software engineering, for research positions in industrial research and development (e.g., application areas, distributed networks, embedded/critical systems), and for leadership positions in development in both computer industry and application shops.

• BEng elective group options
• Software Engineering (MEng)
• Software Engineering (MASc)
• Software Engineering (PhD)

Key resources

• Graduate funding
• Tuition and fee estimator
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© Concordia University

We have 26 Latest Software Engineering PhD Projects, Programmes & Scholarships

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Latest Software Engineering PhD Projects, Programmes & Scholarships

Ai meets crime linkage, phd research project.

PhD Research Projects are advertised opportunities to examine a pre-defined topic or answer a stated research question. Some projects may also provide scope for you to propose your own ideas and approaches.

Competition Funded PhD Project (Students Worldwide)

This project is in competition for funding with other projects. Usually the project which receives the best applicant will be successful. Unsuccessful projects may still go ahead as self-funded opportunities. Applications for the project are welcome from all suitably qualified candidates, but potential funding may be restricted to a limited set of nationalities. You should check the project and department details for more information.

Automated mHealth Application Development: A Case Study on the P-STEP App for Atrial Fibrillation

Sensor-driven robotic automation for high-integrity welding in marine structures, funded phd project (european/uk students only).

This project has funding attached for UK and EU students, though the amount may depend on your nationality. Non-EU students may still be able to apply for the project provided they can find separate funding. You should check the project and department details for more information.

Doctoral Research Associate (EU-Forscher*in. salary level E 13 TV-L, 100%)

Funded phd project (students worldwide).

This project has funding attached, subject to eligibility criteria. Applications for the project are welcome from all suitably qualified candidates, but its funding may be restricted to a limited set of nationalities. You should check the project and department details for more information.

Development of broadband electronic warfare sensors for signal detection and direction finding

Media sector climate impacts and sustainability interventions (bbc r&d), unlocking the full potential of eeg: a data-driven approach to functional neuroimaging in the absence of mri, expanding the capabilities of the molecular simulation design framework (mosdef), school of computing science, funded phd programme (students worldwide).

Some or all of the PhD opportunities in this programme have funding attached. Applications for this programme are welcome from suitably qualified candidates worldwide. Funding may only be available to a limited set of nationalities and you should read the full programme details for further information.

Computing PhD Programme

PhD Research Programmes describe the opportunities for postgraduate research within a University department. You may often be asked to submit your own research project proposal as part of your application, although predefined research projects may also be available.

Learning Caching Strategies for Dynamic Workloads on Graph Databases

Funded phd project (uk students only).

This research project has funding attached. It is only available to UK citizens or those who have been resident in the UK for a period of 3 years or more. Some projects, which are funded by charities or by the universities themselves may have more stringent restrictions.

PhD in Post-Quantum Cryptography

Unveiling tipping points in lakes, developing digital twin and digital product passports for high-value electric machines to support their end-of-life decisions, doctoral research associates (eu-forscher*in, salary level e 13 tv-l, 100%), hot spots and pressure points: developing ai to identify normal and pathological periprosthetic osteoblastic activity for total knee arthroplasty on spect/ct.

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Doctoral study in Software Engineering

Why study with us.

• The highest-ranked engineering faculty in New Zealand (QS World University Rankings by Subject, 2021)
• Opportunities to be supervised by experts in the field, such as world-class researchers in the areas of Human Aspects of Software Engineering , Parallel and Reconfigurable Computing , and Software Engineering for Robotics
• Connections to professional, industry and research organisations, including the Association of Computing Machinery (ACM) and Software Innovation New Zealand
• Access to Postgraduate Research Student Support (PReSS) funding for research expenses

Research opportunities

Pursuing a PhD at our University gives you access to a high-calibre research community – you may have the opportunity to publish papers, attend international conferences, and develop your network in academia and industry.

We welcome research proposals in topics relating to our key areas, including:

• Human and social aspects of software engineering , with emphasis on the people involved in software development processes, including studying ways to improve coordination on software teams, improving comprehension of software programs, and devising novel techniques to help software developers understand what users want from the software. 
• Software testing , which involves studying the ways to improve the verification of software systems, such as non-determinism in testing (test flakiness), test oracle generation/improvement, automated software testing, and testing of concurrent software programs.
• Machine Learning for software engineering , focusing on best practices in designing and developing software solutions with machine learning algorithms at the core. Applied Machine Learning, including designing systems for autonomous vehicles, intelligent and automated health care systems, automatic speech recognition for the speech impaired, and speaker identification and verification.
• Parallel and reconfigurable computing , including task scheduling for parallel systems, reconfigurable computing with FPGAs, reliability in scheduling, and design of novel scheduling algorithms. 
• Software security , including examining novel approaches for the mitigation of attacks in Cyber-Physical Systems (CPS), such as medical devices and smart grids. Digital educational engineering to improve student learning by applying the software engineering process with the latest technologies, including machine learning, virtual reality, augmented reality, and more. 
• Software engineering for robotics , including improving software tools and processes for robotic drivers and speech systems.

Dr Kelly Blincoe is an expert in the human aspects of software engineering. Her research focus is on collaborative software development. She studies software dependencies and the resulting coordination needs between software developers. She was awarded a Marsden Fast Start grant to investigate new techniques to automate software dependency updates, which can enable more secure software products. She also does research in software requirements engineering and diversity and inclusion on software teams. Kelly is a leader in the International Software Engineering research community. She is an Associate Editor of the IEEE Transactions on Software Engineering, the Empirical Software Engineering Journal, and the Journal of Systems and Software. She serves on the executive committee of Software Innovation New Zealand and is the Diversity, Inclusion, and Belonging co-chair for the ACM’s Special Interest Group on Software Engineering.

More experts in Software Engineering:

• Professor Bruce MacDonald
• Associate Professor Catherine Watson
• Dr Craig Sutherland
• Dr Jesin James
• Dr Kevin Wang
• Dr Nasser Giacaman
• Dr Nitish Patel
• Associate Professor Oliver Sinnen
• Professor Partha Roop
• Dr Reza Shahamiri
• Dr Valerio Terragni

Past research topics

• Task Allocation in Agile Software Development Teams | Supervised by Dr Kelly Blincoe and Dr Rashina Hoda
• Automated software test oracle | Supervised by Dr Reza Shahamiri
• Cloud Computing with Annotation Parallel Task (@PT)  | Supervised by Associate Professor Oliver Sinnen and Dr Nasser Giacaman
• Program Comprehension Challenges Detection For Pull Requests With Machine Learning | Supervised by Dr Kelly Blincoe
• Deep Neural Network-based Speaker Identification | Supervised by Dr Reza Shahamiri
• Optimal Task Scheduling for Parallel Systems using State-Space Search | Supervised by Associate Professor Oliver Sinnen and Dr Avinash Malik
• Formal Methods for functional Safety of Industrial Automation Systems | Supervised by Professor Partha Roop
• Robot application programming interface and language design | Supervised by Professor Bruce MacDonald , Dr Beryl Plimmer, and Professor John Hosking

Scholarships and awards

There are several scholarships you may be eligible for when you decide to pursue your PhD in Operations Research, including the University of Auckland Doctoral Scholarships .

Help and advice

For general student enquiries, please contact the Student Hubs.

If you would like to find out more about studying Software Engineering, you can contact a Postgraduate Adviser .

Apply for doctoral study

Doctoral programmes.

• Doctor of Philosophy

Related subjects

• Computer Systems Engineering
• Electrical and Electronic Engineering

Related links

• How to apply

PhD Research Topics in Software Engineering

“Software Engineering comes as an eternal research area. Generally, it plays a vital role in so many domains. It is the key choice to grow our research works.” PhD Research Topics in Software Engineering  will create not only lengthy research but also a great one. In general, our experts will finish your research at the right time. Owing to their 18+ years of skill, this is possible.

MAJOR FEATURES OF PREFERABLE SOFTWARE

• GUI based modern infrastructure for large scale/complex system
• Open-source platform independent
• Flexible to incorporate external tools
• Reliable and also Robust to recover information
• Secure and also Private accessibility

PhD Research Topics in Software Engineering  will take off your research against every hurdle like an airplane. We will give the workspace with better services for you. To fulfill the overall wants set by you, we will craft a plan. Evidently, we will share this with you and get your opinion.

TOP AREAS assisted by  PhD Research Topics in Software Engineering

Cloud computing, big data analytics, data mining, digital image processing, artificial intelligence.

• Internet of Things
• Augmented and also Virtual Reality
• Mobile-Edge Computing
• Pervasive and also Ubiquitous Computing
• Brain Computer Interaction
• Green Computing

We will also help in your paper writing under any one of the areas, as shown above. In the same way, we will make the perfect report for you with good value. Your paper will also go through a thorough review before we send it to you.

In sum, we have 150+ experts to do your research work. After your research is over, you can contact us for further aid. Besides, we will also offer an N-number of revisions to fulfill your needs.

We have given some more abstract topics in this field for you,

A novel technology for Identification of fake reviews used by semantic and behavioral features scheme

A novel Sources of Satisfaction in Agile Software Development system

An innovative method for Assessment Model to Foster the Adoption of Agile Software Product Lines in Automotive Domain

A new method for Rise and Evolution of Dynamic function of  Software engineering Development

An effective mechanism for Mapping Study based on Knowledge Management in Agile Software Development

Modern method for Modeling the Dynamics of an Agile Scrum Team in the Development of a Single Software Project

The firsthand function of Perceptions based on Diversity in Brazilian Agile Software Development

An effective mechanism for Mobile Search  based In-depth Analysis in  ontexts, APPs, and Devices

A new process of Beyond Web/Native/Hybrid Taxonomy for Mobile App Development

An efficient mechanism for Progressive web based on alternative to native mobile Apps

On the use of Preliminary Investigation of Predicting Next-Use in Mobile Depictions

An effective method for Automated Cross-Platform GUI Code Generation for software based Mobile Apps

A new-fangled process of  User-Friendly Low-Cost Mobile App Based on Home Appliance Control And Circuit Breaker

A novel process of Large-Scale Analysis for Framework-Specific Exceptions in Android Apps

A new method for Positive and Unlabeled Learning intended for User Behavior Analysis Based on Mobile Internet Traffic Data

An effective function of Collaborative Offloading for Distributed Mobile-Cloud Apps

Design and development based on Machine Learning for Software Engineering Models, Methods, and Applications systems

An innovative performance for Effective Engineering of Multi-robot Software Applications

An inventive method for Matrix of Analyzing Projects in Software Engineering Paths

An effective mechanism for intention towards Building a Sustainable Structure designed for Research Software Engineering Activities

Why Work With Us ?

Senior research member, research experience, journal member, book publisher, research ethics, business ethics, valid references, explanations, paper publication, 9 big reasons to select us.

Our Editor-in-Chief has Website Ownership who control and deliver all aspects of PhD Direction to scholars and students and also keep the look to fully manage all our clients.

Our world-class certified experts have 18+years of experience in Research & Development programs (Industrial Research) who absolutely immersed as many scholars as possible in developing strong PhD research projects.

We associated with 200+reputed SCI and SCOPUS indexed journals (SJR ranking) for getting research work to be published in standard journals (Your first-choice journal).

PhDdirection.com is world’s largest book publishing platform that predominantly work subject-wise categories for scholars/students to assist their books writing and takes out into the University Library.

Our researchers provide required research ethics such as Confidentiality & Privacy, Novelty (valuable research), Plagiarism-Free, and Timely Delivery. Our customers have freedom to examine their current specific research activities.

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Bengaluru engineer, who has been on NIA most wanted list since 2012, emerges as handler of three terror modules in Karnataka

He is an engineering graduate (2004-2008) from ramaiah institute of technology, bengaluru.

Updated - September 10, 2024 09:54 am IST - Bengaluru

Mohammed Shahid Faisal, the alleged handler of three terror modules in Karnataka. | Photo Credit: Special Arrangement

Mohammed Shahid Faisal, said to be 40-years-old and suspected to be based out of Pakistan, has been named by the National Investigation Agency (NIA) as the alleged handler of the terror module that carried out an IED explosion at The Rameshwaram Cafe on March 1, 2024.

Faisal is not a new entity for the Karnataka State Police and security agencies of the country. He has been on the wanted list of the NIA from 2012 and carries a reward of ₹10 lakh. He has now emerged as the alleged handler to three terror modules in Karnataka across 12 years. 

A native of Bengaluru and an engineering graduate (2004-2008) from Ramaiah Institute of Technology, Bengaluru, he worked as a software engineer for a few years in the city. He later left for Saudi Arabia and has not returned. He came on the radar of the Karnataka police for the first time in 2012, when he was known with his alias “Zakir” and “Ustad”, then suspected to be based out of Riyadh, Saudi Arabia. He was named the alleged handler of a Lashkar-e-Taiba-linked terror module in Bengaluru and Hubballi, that was allegedly conspiring to assassinate Hindutva right-wing individuals. He has remained at large since then. 

Son-in-law of Farhatullah Ghori?

Faisal is suspected to have now moved to Pakistan. However, there has been no confirmation, sources said. Faisal is said to be the son-in-law of Farhatullah Ghori alias Abu Sufiyan, hailing from Hyderabad and the alleged mastermind of the 2002 Akshardham attack in Gujarat, designated a terrorist by the Government of India in 2018.

Farhatullah Ghori is also suspected to be based out of Pakistan, where he allegedly runs a terror recruitment and financing cell through which he is said to have groomed several sleeper cells in India. A video of Farhatullah Ghori exhorting sleeper cells in India to attack the rail network in the country and where he goes on to elaborate various methods to rig bombs, was reportedly circulated on Telegram in August 2024 and flagged by the Indian security agencies. 

2012 link to two terror modules

A convict in the 2012 LeT conspiracy case Shoaib Ahmed Mirza, who served a sentence of five years and was released in 2018, introduced the prime accused in The Rameshwaram Cafe case Abdul Matheen Taaha to Faisal, the NIA has alleged.

“Mirza had further provided an e-mail ID for encrypted communication between the handler and Taaha,” NIA said in May 2024, when it arrested Mirza. The interrogation of Taaha and Mussavir Hussain Shazib after their arrest in April 2024, on how they came in contact with their handler “Colonel”, led them to Mirza, who identified the handler as Faisal, sources said. Faisal was also the handler in the 2020 Al Hind module case, but had remained unidentified for years now,

The elusive ‘Colonel’

Faisal was in touch with Taaha and the other accused through encrypted messaging channels online and was known by the names “Colonel” and “Bhai”. Faisal allegedly groomed two terror modules through Taaha since 2018. 

Taaha allegedly introduced Mehboob Pasha, of the Al Hind Trust in Suddaguntepalya in Bengaluru, and Khaja Moideen, from Cuddalore, Tamil Nadu, to Amir of ISIS South India, who wanted to launch an insurgency in the forests of South India. This module, which came to be known as the Al Hind module was busted in January 2020. But Taaha and Shazib managed to give a slip to the agencies and were at large since then. 

Faisal again groomed the duo, financed them through cryptocurrencies, while they were on the run for four years and put together another module which came to be known as the Thirthahalli module, investigations have revealed, sources said. The NIA has uncovered money trail through cryptocurrency transactions between Faisal and Taaha. 

Taaha and Shazib radicalised at least 10 youths from Shivamogga, Chikkamagaluru, and Mangaluru and this module was involved in at least four cases till now - terror graffiti case and cooker blast case in Mangaluru, trial blast case in Shivamogga in 2021, and The Rameshwaram Cafe blast case.

Two senior police officials from the State, who separately probed the 2012 LeT conspiracy case and the 2020 Al Hind module case, said the handler in both the cases, unidentified before the probe went to NIA and now identified as Faisal, was “extremely tech savvy and it took several counter-intelligence measures to cover his trail”.

Published - September 09, 2024 09:38 pm IST

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