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PhD Research Projects at ACFR

Robotic Imaging: Seeing in New Ways

We have multiple openings in robotic imaging. Our team combines optics, algorithms, and machine learning to make new and better ways for robots to see.

Our students push the limits of perception in robotics. Excellent candidates will qualify for full tuition, stipend, and top-up scholarships.

• Machine learning  for camera design and interpretation
• Novel cameras : computational imaging devices spanning single-photon sensors, nano-optics, solid-state LiDAR, femtosecond imaging, event cameras, multispectral, light field imaging…
• Vision for  small and fast  robots: flying, driving, fast manipulation
• Long-range imaging in participating media:  underwater, fog, rain
• Active and  interactive  imaging and control
• Streaming / live virtual reality and telepresence, augmented reality for the vision impaired
• Light field video processing: using  4D cameras  to see where others cannot
• Autonomous driving, underwater survey, drone delivery, robotic surgery

About the lab: https://roboticimaging.org Contact: [email protected]

Control of Walking Robots

As robots move out of controlled environments like factories and into the wider world, many creative methods of locomotion are being explored. In particular, legged robots are suitable for traversing terrain too rough or irregular for wheels. The dynamics of legged locomotion presents many exciting challenges for planning and control: it is nonlinear, uncertain, high-dimensional, non-smooth, and underactuated.

Candidates will investigate one or more of:

• Integrated perception and motion planning over uneven terrain
• Optimization and learning paradigms for provably-robust control policies
• Experimental investigations with the ACFR’s Agility Robotics Cassie robot (pictured left)

Contact: [email protected]

Safeguarding Our Online Social Networks

Today online social networks have fundamentally changed the way how our society is organized. However, the presence of misinformation and disinformation in forms of fake customer reviews, manipulated news, and disingenuous recommendations etc. are posing systemics risks on the well-being of our social members in the short term and the values our society holds in the long term. More importantly, the social interactions between peers may accelerate the spread of misinformation and amplify the harm from adversarial actions as we live in an interconnected network. Recently, in collaboration with researchers from University of Texas Austin, University of Oxford, and Chinese University of Hong Kong we uncovered the hidden risks of our social interactions being identified from public records on social networks ( https://dx.doi.org/10.2139/ssrn.3875878 ). This projects aims to develop algorithms and optimization frameworks by which we slow down the spread of misinformation and safeguard our social networks, using tools from control theory, optimization, and machine learning.

Contact: [email protected]

LiDAR Pointcloud Perception and Deep Learning in Forests

The ACFR is currently engaged in several national and international collaborations with research, industry and government partners in sensing and robotic applications in commercial forestry, forest health, ecology and management. Forests are structurally diverse environments that pose unique challenges for robotic sensing and perception. This research will aim to develop new methods for sensing, perception and navigation using LiDAR, photogrammetry and hyperspectral imaging in forests.

Candidates will investigate one or more of the following topics:

• New developments in deep learning models for 3D pointcloud data
• Human-computer interaction for 3D deep learning using virtual reality
• Applications of 3D robotic perception and learning in forest environments

Contact: [email protected]

Sensing and Mapping the Dynamic World

Dynamic scenes challenge a number of mature research areas in computer vision and robotics, including simultaneous localisation and mapping (SLAM), 3D reconstruction, multiple object tracking etc. Most of the existing solutions to these problems rely on assumptions about the static nature of either the environment or the sensing modality. This drastically reduces the amount of information that can be obtained in complex environments cluttered with moving objects. To achieve safe autonomy, obstacle avoidance and path planning techniques require this information to be integrated.

• Robust segmentation and tracking of moving objects sensed by a sensor (camera, laser) in motion.
• Simultaneous localization and mapping of dynamic environments.
• Novel representations of dynamic scenes directly connected with the requirements of the autonomous vehicles.

Contact: [email protected]

Marine Robotics

We undertake fundamental and applied research in a variety of areas related to the development and deployment of marine autonomous systems. The ACFR, as operator of a major national Autonomous Underwater Vehicle (AUV) Facility, conducts AUV-based surveys at sites around Australia and overseas. These AUV surveys are designed to collect high-resolution stereo imagery and oceanographic data to support studies in the fields of engineering science, ecology, biology, geoscience, archaeology and industrial applications.

One of the major challenges with this program is managing, searching through and visualizing the resulting data streams. Our recent research has focused on generating high-fidelity, three-dimensional models of the seafloor; precisely matching survey locations across years to allow scientists to understand variability in these environments; and identifying patterns in the data that facilitate automated classification of the resulting image sets.

Providing precise navigation and high-resolution imagery lends itself to novel methods for data discovery and visualization. As a result, we have a strong focus on methods for interacting with and discovering patterns in the data using machine learning techniques. We also have a strong record of engagement with end users in a variety of domains interested in understanding marine environments.

• Platforms and sensing : autonomous marine vehicles, high-resolution stereo imaging, hyperspectral, lightfield imaging
• Navigation and mapping : SLAM using both visual and acoustic data, visualization
• Planning and Control : information based planning, low level control and in particular in manipulation and intervention
• Data Analytics : automated processing of large volumes of data, automatic registration of multi-year datasets, identification of direct change as well as distributions of organisms

Contact: [email protected]

Intelligent Transportation Systems

Driving the development of future mobility

Intelligent transportation systems (ITS) research is vital for improving future mobility around Australia. By investigating and developing new technologies, ITS can help make our roads and transport networks safer, more efficient and more sustainable.

Research in ITS now will pay dividends for generations to come. It is essential for keeping Australia moving forward into the future – literally!

Our research spans various autonomous vehicle technologies, including:

• Sensor fusion for perception and tracking
• Autonomous vehicle navigation and control
• Pedestrian intention prediction
• Connected autonomy, cooperative perception and planning
• Designing the interactions between vehicles and pedestrians

Contact: [email protected]

Radar Acoustic Systems

• This project aims to quantify small-scale air turbulence using Doppler returns from a Radar Acoustic Sounding System (RASS) at standoff ranges. The newly discovered ability of strobed Schlieren to provide images of ultrasonic sound fields is significant as it will be exploited to visualise the changes in this field structure when passing through turbulent air. These changes will then be correlated with the simultaneously measured micro- Doppler returns from the RASS. Once this relationship is understood, we can dispense with the Schlieren setup, and rely on the RASS to provide a measure of the air turbulence.

Contact: [email protected]

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Australian Centre for Robotics [email protected]

PhD Scholarships

Our PhD Scholarship program offers students funding to work alongside some of the world’s leading quantum researchers and gain industry-ready skills.

PhD Scholarship: Key dates

Open date: 10 April 2024

Close date: 15 May 2024

Use the link below to apply for the SQA PhD and/or the SQA Partnership PhD Scholarship.

Ensure that you have reviewed the conditions of award and the application guidelines in the table below.

Not ready to apply in this round? Sign up to our mailing list to hear about future scholarships rounds.

Be part of world-leading quantum research 

Are you passionate about conducting innovative research in the field of quantum science and technology? The following PhD Scholarships are available:

SQA PhD scholarship: These scholarships are for outstanding international and domestic students to collaborate with a team of leading researchers on innovative research at one of our partner universities: Macquarie University*, UNSW Sydney, the University of Sydney, and the University of Technology Sydney*. Includes participation in our exclusive PhD Experience Program.

SQA Partnership PhD scholarship : These scholarships are for outstanding international and domestic students to undertake research projects co-designed and supervised by researchers from UNSW Sydney and CSIRO. Includes participation in our exclusive PhD Experience Program.

Both of these scholarships offer exclusive access to the SQA PhD Experience Program  connecting you with a vibrant community of fellow quantum PhD students across Sydney. Additionally, you’ll have the opportunity to undertake coursework at our partner universities, and participate in training, exclusive seminars and workshops designed to give you a competitive edge in the future quantum workforce. You’ll also network with the brightest minds in quantum research and enjoy career development opportunities within academia and related industries.

*The SQA PhD scholarship aims to address gender imbalance among students pursuing a career in quantum technology. Therefore, for reasons of building greater diversity, scholarship places at Macquarie University and University of Technology Sydney will be reserved for students who identify as women.

If you are a domestic student, you may also be eligible to apply for the Next Generation Quantum Graduates Program Scholarship (NGQGP).

Here’s why our scholarships stand out:

Expert supervisors.

Our partner universities are home to over 100 leading quantum researchers who have made breakthrough discoveries across quantum disciplines and applications.

Cutting-edge Facilities

Access state-of-the-art labs and equipment, providing an optimal environment for your research.

Exclusive access to our PhD Experience Program

Our PhD Experience Program is designed to expand  quantum knowledge and provide career development through exclusive workshops, seminars, and a range of coursework offerings across our partner universities.

Vibrant PhD student community

Discover boundless opportunities and camaraderie within our vibrant student community. Connect with peers and academics from our partner universities and cultivate enduring friendships at our organised events throughout the year.

Strong Industry Partnerships

Collaborate with industry leaders, enhancing practical applications and real-world impact.

Startup Incubator

Our universities foster innovation , creating an ecosystem where quantum-related start-ups thrive.

How do I find a supervisor and/or project?

For SQA PhD Scholarship:  Explore our quantum research opportunities to find a research project that sparks your interest or search our database of Sydney Quantum Experts to find a potential supervisor for your research area of interest. For more guidance, view our guide on ' How to apply for a quantum PhD in Sydney .

For SQA Partnership PhD Scholarship:  Discover the research projects that are available. You will need a relevant research proposal for one of these projects and an endorsement from the specific research supervisor.

What our PhD students say

Hear from our PhD Scholarship students on the benefits of being part of the Sydney quantum community. Read more student stories.

SQA PhD candidate at Macquarie University

"SQA has something that most places are lacking – this peer network" said Riddhi Ghosh. "This was very helpful when I moved to Australia. Most of the friends I had for the first one and a half years were from SQA."

Pursuing your passion – and making friends

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Working at the intersection of light and matter 

Read more of the post Working at the intersection of light and matter 

What it's like to study a PhD in quantum technology

Watch the video to hear from our PhD Scholarship students on the benefits of being part of the Sydney quantum community.

Watch now of the video What it's like to study a PhD in quantum technologyl

How to apply for a quantum PhD in Sydney

If you ’re excited  to pursue a quantum PhD at one of our partner universities, we’ve developed a helpful guide on how to apply. It’s full of important information that you need to know before applying for your SQA PhD Scholarship.

To be eligible for an SQA PhD Scholarship, you need to apply for or be enrolled in a full-time PhD program at one of our partner universities.

Application details

What do the scholarships offer.

SQA PhD Scholarship:

This scholarship is funded by the New South Wales Government and our partner universities.

There are four streams of the SQA PhD Scholarship, each offering the following:

Stream 1: The SQA Primary Scholarship

• A stipend worth AU$37,684 (2024 rate) per annum (pro rata) for the period of the recipient’s PhD candidature, for a maximum of 4 years (full-time equivalent). The stipend will be reviewed at the end of each year.
• International tuition fees waived for international recipients. Other fees for international recipients, such as visas costs or overseas health cover, may also be covered at the discretion of the University and will be advised at the time of offer.
• Entry to the  SQA PhD Experience Program . Completion of the program is required.
• Access to SQA career development funding.

Stream 2: The SQA Supplementary Scholarship 

• A small stipend top-up worth the difference of the recipient’s primary PhD stipend and the SQA Primary Scholarship (pro rata and reviewed annually) for the period of their primary PhD stipend.
• International tuition fees waived or covered for international recipients for any period not covered by their primary PhD stipend scholarship. Other fees for international recipients, such as visas costs or overseas health cover, may also be covered at the discretion of the University and will be advised at the time of offer.
• A stipend extension will be applied at the end of your primary PhD stipend, taking your total candidature to a maximum of 4 years. The funding amount provided will be the SQA rate at that time and will be at least equivalent to your university stipend rate.

Stream 3: The SQA Supplementary Extension Scholarship

• This scholarship is a stipend extension that will be applied at the end of your primary PhD stipend, taking your total candidature to a maximum of 4 years. The funding amount provided will be the SQA rate at that time and will be at least equivalent to your University stipend rate.

Stream 4: The SQA PhD Experience Program Scholarship

• Non-stipend scholarship
• Entry to the  SQA PhD Experience Program .
• Access to SQA career development funding (subject to availability).

SQA Partnership PhD Scholarship :

This scholarship is funded by CSIRO and supported by SQA, and offers:

• A stipend of at least AU$37,684 p.a.
• A training allowance.

Am I eligible?

SQA PhD Scholarship and SQA Partnership Scholarships: 

• Domestic students include Australian citizens, permanent residents, a person entitled to stay in Australia, or to enter and stay in Australia, without any limitation as to time and a New Zealand citizen.
• International students must either hold or be able to obtain a valid visa for the duration of the specified term upon being awarded the scholarship.
• You must be a student who has commenced or is due to commence your PhD studies from Jan 2024 - October 2024. International students may also commence in the first half of 2025. Students who commenced in 2023 or prior are not eligible.

SQA PhD Scholarship: 

• You are expected to apply for or be enrolled in a full-time PhD program at an SQA partner university. PhD projects must be in a field related to quantum technology. Please note you will not be offered an SQA PhD scholarship unless you have a PhD offer of admission.
• You must have the support of an academic staff member at one of the partner universities. To help you find a potential supervisor, view our list of the  latest quantum research opportunities  or search our  Sydney Quantum Expert list . For more guidance, view our guide on ' How to apply for a quantum PhD in Sydney .

Stream 1: The SQA Primary Scholarship:

• You must not hold another primary PhD stipend scholarship (for example, a Research Training Program (RTP) or equivalent scholarship).

Stream 2: The SQA Supplementary Scholarship: 

• You must hold, or have an offer to hold, a primary PhD stipend scholarship (for example, a Research Training Program (RTP) or equivalent scholarship).

Stream 3: T he SQA Supplementary Extension Scholarship:

• Your primary PhD stipend scholarship must be of a length less than 4 years (full-time equivalent).

Stream 4: The SQA PhD Experience Program Scholarship:

• You can be a student at any stage of your PhD at an SQA partner university, although you must have at least an unconditional offer of admission at the time of application. We strongly recommend you apply after you are already enrolled.

SQA Partnership PhD Scholarship

• Before submitting your application, it's essential to secure the support of the project supervisor. Please refer to the list of projects and supervisors associated with this scholarship.
• You must not hold another primary PhD stipend scholarship (for example, a Research Training Program (RTP) or equivalent scholarship).  

We encourage applicants based overseas to apply . If you are based overseas, and not currently an Australian resident or holder of a permanent resident visa, your application will be considered for the main SQA scholarship program.   You may be able to commence your studies overseas if you have support from your supervisor and university, and have received your visa, however, you may not be able to start receiving scholarship payments until you arrive in Australia and/or have an Australia bank account.   Please check with your university for further information on offshore commencement.  

Before you apply

Before submitting your application, please read the relevant documents listed below related to your preferred scholarship:

• Application Guidelines
• Conditions of Award

Supporting documentation

To be considered for a stipend scholarship, please upload the following documents with your application. This supporting documentation must be contained in a single pdf (not a portfolio).

• Project proposal
• Academic transcript(s)
• Any other information supporting your application

Supervisor endorsement

When you submit your application, an email will be sent to your proposed supervisor for them to complete a supervisor endorsement form. In order to receive an endorsement, you need to have previously communicated with your proposed supervisor, and they must have agreed to supervise you.

PhD Experience Program Scholarship (non-stipend)

The application process for the PhD Experience Scholarship does not require supporting documentation. In the application form you will be asked for details about yourself and your PhD - including a brief description of your research project/area (max 200 words).

You will also need the support of your supervisor, and they will asked to endorse your application once completed.

Please note: Failure to follow the guidelines will lead to your application not being considered.

For SQA PhD Scholarship:  Explore our quantum research opportunities to find a research project that sparks your interest or search our database of Sydney Quantum Experts to find a potential supervisor for your research area of interest. Projects suit both experimentalists or theorists, and driven individuals with backgrounds across a range of disciplines such as physics, computer science, engineering, chemistry or mathematics. For more guidance, view our guide on ' How to apply for a quantum PhD in Sydney .

How will my application be assessed?

SQA PhD Scholarship: Primary, Supplementary and Supplementary Extension Streams

Applications will be assessed based on the following criteria:

• Candidate experience including academic merit, experience in quantum technology and / or any professional expertise
• Quality of the proposed project including relevance to quantum technology and / or alignment to the research strengths of the proposed partner institution
• Alignment of the application to SQA objectives including industry engagement, cross-institutional supervision and / or the potential to contribute to the growth of Sydney’s quantum ecosystem.

Consideration will also be given to supervisor capacity, diversity of applicants and the diversity of the proposed supervisors (early to mid-career supervisors and supervisors who identify as women).

The SQA encourages applications from women, Indigenous Australians, applicants with culturally and linguistically diverse backgrounds, people with disability, and from those who identify as LGBTIQ. We welcome applicants to include this information as part of their applications.

Applications will be assessed by researchers and academics within the four partner universities through a competitive assessment process. You should ensure that all information conveyed in your application can be understood by someone within and outside your sub-discipline.

SQA PhD Partnership Scholarship

Applications will be assessed by SQA and CSIRO, based on the following criteria:

• Quality of the proposed project including relevance to quantum technology and alignment to the proposed project by UNSW and CSIRO supervisors.
• Candidate experience including academic merit, experience in quantum technology and / or any professional experience

What is SQA career development funding (CDF)?

• All SQA PhD scholarship students (Primary, Supplementary, Supplementary Extension and PhD Experience) will have access to a pool of SQA career development funds held locally at your university. The approval processes and availability of funds will depend on your university who manage the process.  The intention of this funding is not to replace funding you may already be eligible to receive (e.g., you may already have support for a laptop from your research group), but rather to provide you with opportunities you may not have been able to access without the SQA CDF - such as specialist training.
• SQA PhD Partnership Scholarship students will have access to career development funding.

How do I know which stipend scholarship type I am eligible for?

•  Please refer to the eligibility requirements in the drop-down menu above. When you submit your application, you will have the option to select if you're applying for a SQA PhD Scholarship or SQA PhD Partnership Scholarship. You do not need to declare which SQA PhD scholarship stream you want to apply for. Based on the answers you provide in your application, we will determine which type of stipend scholarship (Primary, Supplementary, Supplementary Extension) you are eligible for.

Can I apply for both the SQA PhD scholarships and the SQA PhD Partnership Scholarship?  

• Yes, you can. In the application form, you will be asked which scholarship you wish to apply for, and you can select either or both.

How many rounds are there per year?

• We typically hold two scholarship rounds per year – one in April and another in September. You can subscribe to our mailing list to be notified when scholarship rounds open.

How do I know if my research area sufficiently relates to quantum tech?

• As quantum tech can span various disciplines and areas, the best person to answer this question is your proposed supervisor.

My supervisor is not on the SQA expert list – does this matter?

• You are most welcome to apply with a supervisor who is not on the SQA expert list, but you still must have a supervisor from an SQA university, and the project must be sufficiently related to quantum tech.

Do I have to come to Australia, or can I do my PhD entirely remotely and apply for a scholarship?

• As per the requirements of your university candidature (see their degree resolutions for details), you will need to do your PhD largely in Australia. You may be able to be overseas for a period within this or commence offshore for a period of time. If you are an international student, you will need an Australia visa granted before you can enrol.

What are the selection criteria?

• Details are available above – under ‘How will my application be assessed?’

Is there an IELTS requirement for a scholarship application?

• There is no SQA specific requirement for IELTS. You will need to adhere to the IELTS requirements of your chosen SQA university however, to be admitted for your PhD. SQA university PhD admission will be required to receive your scholarship, should you be awarded.

Do I need to include my co-supervisor in my application?

• It is not required if you have not organised a co-supervisor at the time of application. You are most welcome to note your co-supervisor in your application if you have one organised.

Can I start my application form and save it to finish it later?

• Depending on your browser – it should remember you and let you return to the same spot. However, if you open it up on a different browser or device, it likely won’t remember you, so make sure to keep a copy of anything you worry about losing to be safe.

I’ve accidentally submitted something incorrect on my application – how do I update this?

• If you submit multiple applications, we will use the latest application you submitted before the deadline in the assessment and selection process. If you are having trouble accessing the form after your first submission (i.e., the link takes you to a thank you for submitting page), if you open the link using a different browser application (e.g. Firefox instead of Chrome) and it should let you access the form anew. Alternatively, you can also email [email protected]  with your updated information.

Can I apply for an SQA scholarship and another scholarship at the same time?

• Yes, you can. However, should you be successful for another scholarship it may change your eligibility in terms of SQA scholarship types. For example, should you receive a non-SQA primary stipend (e.g., an RTP) since your application, you would no longer be eligible for an SQA Primary Scholarship, but you still may be eligible for an SQA Supplementary Scholarship.

Can I do an internship during my PhD?

• For the SQA PhD Scholarships, we are very supportive of you doing an internship during your candidature –  we have more information on internships here .  Note, you will likely need to get approval from your supervisor and university and follow any of their requirements.

Can I get a second extension (past 4 years) if my thesis is delayed?

• In general, no. This is due to most university degree resolutions stating that four years full time (not including extended leave or suspensions of study) is the maximum candidature length. See your university’s degree resolutions for details.

Can I reapply if I am unsuccessful?

• Yes, you are most welcome to reapply in future rounds, as long as you still fulfil the eligibility criteria.

Can I get feedback on my application?

• Unfortunately, we cannot provide feedback on your application.

Can I apply if I am a cotutelle students with an SQA university and another university?

• Yes, you can apply. Should you be successful however, the SQA PhD Scholarship stipend would only cover the period you are in Sydney and based at the SQA university.

I have another question not answered here – who can I ask?

• Please email  [email protected]  and we will get back to you as soon as possible.

Ready to apply?

Applications for Round 10 opens on the 10th of April 2024. Before submitting your application, please read the relevant documents listed below:

Applications are open all year round. Apply  here for the PhD Experience Program scholarship.

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PhD student opportunities

Our PhD students play a crucial role in a diversity of key projects, gaining valuable experience and expertise while contributing to research and development outcomes.

Be at the leading edge in your field

Ready to shape the future? To discuss existing or potential projects  contact us

New PhD candidates have the opportunity to become involved in our projects across multiple areas, including those listed below.

A. Applied electromagnetics and antennas

Sponsored by the Australian Research Council (ARC), this project is to develop a novel reconfigurable antenna array structure and beamforming algorithms to increase the distance and data rates of wireless communications between air-borne/space-borne vehicles.

TeraHertz (THz) antennas

THz is regarded as the next frontier for wireless communications and sensing. The challenges are in ultra-high gain antenna design, integrated design of the antennas and THz front-end, and a new generation of wireless system architecture to manage the characteristics and THz waves. Sponsored by industry, this project will address these challenges through theoretical and experimental studies.

Base station antennas for 5G wireless communications

The cellular wireless communications industry is moving towards 5G, in turn demanding more advanced antennas and bringing challenges relating to massive antenna arrays, the capability to deal with more bands, and low-cost mm-wave antenna systems. This project aims to develop new antenna technologies to meet the capacity requirements of future 5G systems.

Base station antennas using metamaterial

Base station antennas are the key devices in wireless cellular communications that provide a link between base stations and mobile stations. The multi-generations of wireless communications systems have posed ever-increasing challenges to the design of base station antennas, particularly around wide bandwidth, beam consistency and polarisation isolation. Sponsored by industry, this research will investigate new antenna configurations and meta-material structures to meet these changing needs.

Frequency and pattern reconfigurable antenna for cognitive radio systems

It is suggested that two separate antennas are required for cognitive radio systems: a wideband antenna for scanning the spectrum, and a narrowband frequency reconfigurable antenna for communicating. This research looks at ways to combine the two antennas together to reduce the size and complexity of the system’s radio frequency (RF) front-end, using a single-port fed antenna that can switch between the wideband and narrowband operations. Additionally, this new development will allow the main beam for each narrowband operation to be steered according to the channel conditions.

B. Wireless communications and remote sensing

Self-interference cancellation for full-duplex wireless communications.

Full duplex has emerged as a new communications paradigm shift and is anticipated to significantly increase information transmission capacity compared to conventional half-duplex radios. This research investigates the theory and implementation techniques for RF and baseband interference cancellation, enabling bi-directional transmission with the same frequency band. Additional uses for full duplex in wireless systems, such as active radar systems, will result in revolutionary architecture innovation and significant performance improvement.

Massive hybrid antenna array for mm-wave communications

Wireless communications using millimetre wave (mm-wave) frequency bands have developed from niche market applications into potentially global applications in mobile broadband systems. Wireless system designers have embarked on research into fifth generation (5G) cellular systems to meet exponential growth in demand for high data rates and mobility required by new wireless applications. This research project will enable the 5G vision, with a focus on development and delivery of a low-cost massive hybrid antenna array implementation and effective digital signal processing techniques.

High-speed signal processing and implementation for wireless communication systems

Increasing demand for high-speed wireless communications systems means that new signal processing algorithms and hardware implementations are necessary to meet low cost and high-performance requirements. This research project will investigate effective digital signal processing algorithms and efficient hardware design to realise high-speed wireless communications in real-time. PhD candidates should have both theoretical background and hardware implementation experience.

C. Data processing

Fine-grained activity recognition and object tracking.

Recognising human activities from video streams is an important task for home automation, robotics and surveillance. Increasingly, human activities need to be recognised at a fine grain, for example, telling apart a person holding a cup of coffee from a person holding a foreign object. In this PhD project, the candidate will investigate the synergistic use of activity recognition and tracking techniques to achieve accurate, fine-grained recognition of activities. The outcome will be a technology that can be flexibly employed in a variety of human-computer applications.

Joint activity recognition and summarisation of videos

Recognising human activities in video clips is an important task for social media analysis. Moreover, being able to automatically select a few frames to summarise each clip (‘storyboarding’) can add extra useful information for an end user. In this PhD project, the candidate will explore how to provide activity recognition and video summarisation together, leveraging the constructive interactions of these two tasks.

Word embedding for natural language processing

Encoding the semantic and structural relationships between words can prove useful for many natural language processing (NLP) tasks. A successful approach ‘embeds’ the words into a vector space where semantic and structural similarities between words are preserved. In this PhD project, the candidate will explore different embedding approaches and their impact on the accuracy of NLP tasks such as named entity recognition and part-of-speech tagging.

D. Internet of Things (IoT)

Ubiquitous timing.

The Internet of Things is growing around us every day. Soon not only smartphones and computers, but objects of all kinds, will be communicating with and sharing data between themselves and with the cloud. An absolutely critical part of that data are the recorded timestamps of when events occur: did the car hit its brakes before the lights went red, or not? Did my fridge decide to throw out my leg of lamb before the power failure, or because of it? Did my stock order really go through before the crash? IoT applications will grow into an enormously diverse and complex system, and timing will be a key to making applications effective and reliable, and in maintaining order over chaos.   

You will join a timing research project, part of the Network Timing Laboratory research effort, to develop a robust and accurate timing system for the IoT ecosystem. This encompasses both the timing approach within IoT devices and the Internet-based support infrastructure. It will build on the extensive experience in Internet timing, including a state of the art timing testbed, at UTS, and involves the cooperation of both national and international partners.

Required background: excellent knowledge of computer networking, excellent programming skills, and knowledge of time series analysis or related disciplines. A stipend is available to outstanding candidates.

E. UAV/Drone research

Drone energy autonomy.

Outstanding students are sought to work on an exciting new project in Drone Energy Autonomy, aiming to develop a reliable, autonomous infrastructure allowing UAVs (with a focus on quadcopters) to operate as if their range were unlimited. The goal is ambitious and transformative and involves significant experimental and theoretical challenges.  

Required background: a recent mechatronics or robotics undergraduate degree, strong practical skills in multi-rotor UAV development, a strong background in control, and a can-do attitude with a determination to have an impact in the space. Significant experience using C++, Python, Linux, and ROS is necessary. A stipend is available to outstanding candidates.

F. Network security

Trusted timing for the internet of things.

The Internet of Things is expanding rapidly.  Soon IoT enabled objects of all kinds will be communicating and sharing data between themselves and the cloud. A critical part of that data is the recorded timestamps of when events occur, and a key question is, can those timestamps be trusted? The security implications of timestamps which have been fabricated, tampered with, or are otherwise unreliable are enormous, given that decisions by individuals, companies, and software will be based on them in myriad ways. For example, the ordering of financial transactions, acceptance of outdated passwords, timely delivery of parcels, or the predicted location of people could all fail if timestamps are wrong. 

You will join a timing research project to develop a secure and trusted timing system for the IoT ecosystem. This encompasses both the security issues within IoT devices and of the Internet-based support infrastructure. It will build on the extensive experience in Internet timing, including a state of the art timing testbed, at UTS, and involves the cooperation of both national and international partners. 

Required background: extensive knowledge of computer networking, excellent programming skills, and knowledge of time series analysis or related disciplines, and a grounding in traditional network security.

Anomaly detection

For security threats which follow a known pattern, a rule or signature-based approach can be an effective countermeasure, for example, to detect and block attacks in applications like network intrusion detection.  When the attack type is unknown, however, its detection is a far more difficult and subtle problem, often complicated by a lack of clear definitions enabling `signal’, `noise’ and `anomaly’ from being distinguished.

You will develop and evaluate methodologies based on innovative approaches to anomaly detection. These will include non-linear filtering, sketching, sampling, and wavelet analysis. The results will be applied to datasets from Internet data and bio-signals and will contribute creatively to the arsenal of methods used Data Analytics.

Required background: strong mathematical background in areas such as statistics, time series analysis, optimisation, machine learning, and well as strong computer science knowledge and programming experience.

Information theoretic security

Data confidentiality is a critical component of secure data transfer, and much of the digital economy, for example, secure financial transactions, rely upon it. It is typically provided using encryption methods involving secret keys, for example in the well-known RSA cryptosystem. A lesser-known, but very powerful basis lies in Shannon’s Information Theory. Information Theoretic Security is based on the idea of the Wyner Wiretap channel, where an eavesdropper, ‘Eve’, has access to the secret transmission through a channel which is noisier than that between the communicating parties. By intricate and clever coding methods, that extra noise can be made to act like an intrinsic secret key. This approach is capable in theory of providing unbreakable security without the need for secret keys to be exchanged.

The project will build on recent work showing how multiple separate channels (like those found in smartphones: Wi-Fi, cellular Bluetooth) can be exploited to provide a system that provides Information Theoretic security guarantees. The research will focus on expanding and applying these results so that they can be used in real networks to secure the future digital economy.

Required background: strong mathematical background in information theory and optimisation, and well as strong computer science knowledge and programming experience. A background in computer networking and cryptography would be a strong advantage. A stipend is available to outstanding candidates.

G. Data analytics

Graph analytics.

Graph theory is a mature discipline with applications in many domains and is often used to model empirical data. A common feature of real-world datasets, however, for example in social networking, is that they are only partially observed, that is they have elements missing. This can be thought of as a statistical sampling of the underlying graph, and there are many important problems in how to infer characteristics of the full graph from such incomplete measurements.  Even if the datasets are very large, the scale of the true underlying graph is often much, much larger, so this is a non-trivial problem, with important implications for the limits of data analytic methods.

This project will develop scalable methods of graph inference, for example, graph matching, capable of tackling truly large graphs. It will also extend them into the relatively unexplored area of hypergraphs, where the concept of a link from graph theory (effectively a pair of nodes) is generalised to any set of nodes.  Hyper-graphs offer much richer modelling options than graphs and will play an important role in the study of the rich, huge, data sets arising from the digital world.

Required background: strong mathematical background in graph theory and optimisation, and well as strong computer science knowledge and programming experience. A background in statistics would be an advantage. A stipend is available to outstanding candidates.

I enjoy studying in this dynamic research environment. It is a great place for me to develop my research abilities and prepare myself for my future academic career. LEARN MORE about Haihan Sun

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Current PhD projects

» email:  [email protected]

Saeed's research focuses on the development of novel spiking (time based) neural network architectures for sensory and learning systems by incorporating insights from the fields of neuroscience, machine learning and signal processing with particular applications in Lidar and event based vision sensors. The ultimate aim of this project is to develop a suite of alternative computer processor designs and algorithms that are faster, more power efficient and better able to adapt in noisy unpredictable environments in comparison to standard computers.

The standard processors which power our laptops and PCs are marvels of human ingenuity. They are the engines of our information age and represent more than half a century of accumulated research and development. However based on the 1945 design by John von Neumann all such processors share the following properties: They are deterministic, they operate on digital representations of instructions and numbers and they do so in a sequential manner. These properties can create informational bottlenecks that are unsuitable for applications where large amounts of temporal data must be processed in real time, under noisy conditions using minimal power. The growing demand for adaptive, automated, portable systems means that number of such applications is increasing rapidly.

In contrast to standard processors the bio-inspired spiking processor designs which are the focus of this research mimic the way the brain processes information in that they are stochastic, adaptive, distributed and use time itself as the central processing element. With the help of customizable digital hardware platforms called Field Programmable Gate Arrays these alternative processor architectures and algorithms can be rapidly prototyped, tested and compared in performance, power efficiency and speed to traditional solutions against which they must compete. In this way this research aims to probe the large search space of potential solutions to real-time temporal data processing applications.

» email:  [email protected]

Synchronous activities within neuronal networks give rise to neural oscillations, which are thought to be involved in physiological processes. My project focuses on investigating the role of cortical astrocytes in modulating neuronal intrinsic properties, specifically in mediating the transition between different network oscillatory frequencies by manipulating the levels of extracellular K+ through K+ clearance mechanisms.

» email:  [email protected]

Obstructive Sleep Apnoea (OSA) is a condition that affects around 9 of the world's adult population, according to research from the Australian Sleep Health Foundation, and poses serious health concerns with sufferers being more prone to depression, obesity and cardiovascular disease. The goal of Titus' project is to develop a personalised treatment that is efficient, effective and much more comfortable to use. The current treatment and monitoring devices are expensive, uncomfortable, so patients do not adhere to the therapy. This will ensure better compliance and better treatment overall.

» email:  [email protected]

David's project on sub-sensory electrical noise stimulation (SENS) of the peripheral nerve aims to:

• investigate the use of SENS to alleviate peripheral neuropathic desensitisation in patients with peripheral neuropathy associated with HIV-infection;
• investigate the effect of SENS on the pain felt by patients with peripheral neuropathic pain;
• develop a fuller understanding of how sub-sensory electrical noise stimulation interacts with the nervous system, and investigate a means of maximally enhancing sensory function of patients with HIV related peripheral neuropathy;
• develop and test a practical "every-day" treatment for patients with HIV related peripheral neuropathy that uses the information gained in the above points.

Peripheral neuropathy is a common problem associated with aging, diabetes, alcoholism and HIV/AIDS. Patients frequently suffer peripheral neuropathic desensitisation. These symptoms may reduce quality of life and increase the risk of secondary ailments. Restoring the functionality lost due to peripheral neuropathy would greatly improve quality of life and prognosis. Currently there is no treatment available.

» email:  [email protected]

Electrocardiography (ECG) is the most popular non-invasive diagnostic tool for cardiac assessment. Vectorcardiogram (VCG) also has been repeatedly found useful for clinical investigations. Hossein is interested in using machine learning and data mining techniques to investigate ECG and VCG to have better representation of heart activity for diagnosis of cardiovascular diseases. His project involves developing methods for taking advantage of both VCG and ECG characteristics by transforming ECG to VCG. He is also involved in a project to develop a new framework to record ECG using a recently developed device which can record the voltage of right arm, left arm and left leg besides the 12 lead ECG.

» email:  [email protected]

Millions of people all over the world are dealing with peripheral vascular diseases (PVD), which can cause morbidity or even mortality. However, early diagnosis of such diseases can help to prevent their consequences. Elham is interested in investigating biological signals for the use of noninvasive diagnosis, and her project focuses on developing a peripheral monitoring device, called HeMo, which can enable early diagnosis of PVDs. This device has a fabric-elasticated cuff incorporating two electro-resistive band sensors, which enable to measure the changes in blood volume due to both postural changes and arterial inflow. Preliminary results derived from Elham's project shows that this device has the potential to be used for diagnosis of peripheral arterial disease and chronic venous insufficiency. At the moment, Elham is working to develop a user-friendly version of the HeMo device and validate its performance for clinical use. As the sphygmomanometer changed the diagnosis and treatment of hypertensive disease by providing a simple means of measuring blood pressure, it is hoped that this research will do the same for peripheral vascular diseases.

» email:  [email protected]

Ram is exploring using computational auditory models to process multiple music instrument recordings mixed on single tracks titled polyphonic music signal. He plans to design and implement a cochlea-cortical model on digital hardware and intends to use neural networks to investigate its responses using pitch and timbre cues to extract music notes and instruments information respectively. He is also interested in the brain's predictive nature by which it manages its expectation through inference and plans to investigate such effects on note prediction using pitch information.

» email:  [email protected]

James' research focuses on interfaces with the somatosensory system, and attempts to bridge the gap between the biological nervous system and the electronic device. Many challenges exist at the neural interface, but the potential benefits of successfully negotiating these will be techniques that can be used in the restoration of sensation to stroke patients, improved assistive technologies for the elderly and disabled and new methods for the teleoperation of remote devices. Concentrating on the peripheral nervous system, we are seeking to extract a control signal from the efferent pathway suitable for directing an assistive device or prosthetic, and to return feedback from the device via the afferent pathway. This research includes materials engineering of electrodes and interfaces, signal processing to decode and encode sensory and control information, neurobiology and anatomy of the peripheral nervous system,  and computer science and electrical engineering for the construction of the device.

Ying Xu 

» email:  [email protected]

Ying's project encompasses developing a neuromorphic integrated circuit (IC) and system to perform real-time auditory signal recognition and localization tasks simultaneously. This system will model the auditory periphery and mimic the neurobiological architecture present in the human nervous system. In this system, an auditory model will be built to convert input sound into frequency time auditory spectrogram. Furthermore, electronic neural systems for classifying auditory spectrograms and localizing the sound source will also be implemented.

Completed Projects:

Ram Singh (2012)

Ram's MEng project was to develop a real time simulator of cochlear filtering and auditory nerve activity.

Runchun's research project was to build neuromorphic VLSI circuits for spatio-temporal pattern recognition with spiking neurons and adaptive spike propagation delays, based on the concept of "polychronous" networks. He has designed an integrate and fire neuron, an axonal propagation delay circuit, a current synapse and associated circuits using analog VLSI.

One of the fundamental tasks underlying much of computer vision is the detection, tracking and recognition of visual features. It is an inherently difficult and challenging problem, and despite the advances in computational power, pixel resolution, and frame rates, even the state-of-the-art methods fall far short of the robustness, reliability and energy consumption of biological vision systems. Silicon retinas, such as the Dynamic Vision Sensor (DVS) and Asynchronous Time-based Imaging Sensor (ATIS), attempt to replicate some of the benefits of biological retinas and provide a vastly different paradigm in which to sense and process the visual world. Tasks such as tracking and object recognition still require the identification and matching of local visual features, but the detection, extraction and recognition of features requires a fundamentally different approach, and the methods that are commonly applied to conventional imaging are not directly applicable. This thesis explores methods to detect features in the spatio-temporal information from event-based vision sensors. The nature of features in such data is explored, and methods to determine and detect features are demonstrated. A framework for detecting, tracking, recognising and classifying features is developed and validated using real-world data and event-based variations of existing computer vision datasets and benchmarks. The results presented in this thesis demonstrate the potential and efficacy of event-based systems. This work provides an in-depth analysis of different event-based methods for object recognition and classification and introduces two feature-based methods. Two learning systems, one event-based and the other iterative, were used to explore the nature and classification ability of these methods. The results demonstrate the viability of event-based classification and the importance and role of motion in event-based feature detection.

The motivation for project is idea that abstract, adaptive, hardware efficient, inter-neuronal transfer functions (or kernels) are the most important element in neuromorphic implementations of Spiking Neural Networks (SNN) which learn spatio-temporal patterns in hardware. In the absence of such abstract kernels, spiking neuromorphic system must realize very large numbers of synapses and their associated connectivity. The resultant hardware and bandwidth limitations create difficult tradeoffs which diminish the usefulness of such systems. In this thesis a novel model of spiking neurons is proposed. The proposed Synapto-dendritic Kernel Adapting Neuron (SKAN) uses the adaptation of their synapto-dendritic kernels in conjunction with an adaptive threshold to perform unsupervised learning and inference on spatio-temporal spike patterns. The hardware and connectivity requirements of the neuron model were minimized through the use of simple accumulator based kernels as well as through the use of timing information to perform a winner take all operation between the neurons. The learning and inference operations of SKAN are characterized and shown to be robust across a range of noise environments.

Advances in integrated circuit (IC) fabrication technology have reduced feature sizes to the order of nanometres, but have created several problems in IC design, such as lower noise immunity, increased process mismatch, and interconnect bottlenecks. Further, the failure of a few transistors may result in the failure of the entire chip, rendering it unusable. Similar to these problems of transistor failure and device mismatch in ICs, the brain is faced with the problems of heterogeneity of neuronal responses to stimuli and neuronal cell death. The biological nervous system functions well despite these problems, and this motivates us to apply its working principles in IC implementation. In this thesis, we draw inspiration from the brain and discuss how 'stochastic facilitation' can be used to perform useful and precise computation. We explore non-deterministic methodologies for computation in hardware and introduce the concept of stochastic electronics; a new way to design circuits and increase performance in noisy and mismatched fabrication environments. We illustrate this approach by presenting systems for both analogue and digital IC design.

For the analogue system, we propose a generic and trainable architecture, which uses device mismatch and nonlinearities explicitly. In this way, the reduced device matching in newer technologies becomes an advantage, rather than something that needs to be engineered out of the design. We have developed a novel neuromorphic system called a Trainable Analogue Block (TAB), which uses device mismatch as a means for random projections of the input to a higher dimensional space. The TAB framework is inspired by the principles of neural population coding operating in the biological nervous system. Three neuronal layers, namely input, hidden, and output, constitute the TAB framework, with the number of hidden layer neurons far exceeding the number of input layer neurons.

For the digital system, we use a stochastic computation (SC) framework to build massively parallel and low precision circuits to solve complex Bayesian inference problems. An advantage of the SC implementation is that it is robust to certain types of noise, which may become an issue in IC technology with feature sizes in the order of tens of nanometres due to their low noise margin, the effect of high-energy cosmicrays, and the low supply voltage. We present the implementation of two types of Bayesian inference problems to demonstrate the potential of building probabilistic algorithms in hardware. The first implementation, referred to as the BEAST (Bayesian Estimation and Stochastic Tracker), demonstrates a simple problem where an observer uses an underlying Hidden Markov Model to track a target in one dimension. In this implementation, sensors make noisy observations of the target position at discrete time steps. The tracker learns the transition model for target movement, and the observation model for the noisy sensors, and uses these to estimate the target position by solving the Bayesian recursive equation online. We show the tracking performance of the system and demonstrate how it can learn the observation model, the transition model, and the external distractor (noise) probability interfering with the observations. In the second implementation, we show how inference can be performed in a Directed Acyclic Graph (DAG) using stochastic circuits, and this implementation is referred to as the Bayesian INference in DAG (BIND). Our work describes canonical neural circuits, which are the basic building blocks of our models, and shows how these neural circuits can be easily implemented using digital logic gates. An advantage of our framework is that the flipping of random individual bits would not affect the system performance because information is encoded in a bit stream. Our work presents a novel approach for implementing probabilistic networks using simple logic gates, with the ability to perform the computation in real time.

Patrick's research focuses on investigating the mechanisms that underlie tactile decoding. Specifically we seek to understand how information relating to area between the finger pad and object is interpreted and transformed by the brain into a format that is relevant for sensorimotor control during dexterous object manipulation. We are recording tactile afferent signals innervating the glabrous skin of the human finger pad. In addition, we are using a combination of mathematical and signal processing approaches to develop models for the analysis of the data. We hope that this will be a step towards designing robots with dexterous manipulation capabilities, inform the design of sensory feedback devices, and possibly guide the development of new methods to improve upon therapies for individuals with neurological disorders.

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Postgraduate Research Scholarship to Develop Integrated Nano Semiconductor

How to apply.

Apply here.

This scholarship is valued at $33,000 and is tenable for 11 months.

Who's eligible

• have an unconditional offer of admission or being currently enrolled to study full-time in a research degree within the Faculty of Engineering at the University of Sydney.
• hold at least an Honours degree (First Class or Second Class Upper) or equivalent in a relevant discipline.
• be willing to conduct research into integrated nano semiconductor devices and related modelling approaches.

This Scholarship has been established to provide financial assistance to research students who are undertaking research that aims to develop integrated nano semiconductor devices and related modelling approaches.

This Scholarship is funded by the Australian Research Council (ARC) through the scheme Discovery Project (DP190101864).

Terms and conditions

1. Background

a. This Scholarship has been established to provide financial assistance to research students who are undertaking research that aims to develop integrated nano semiconductor devices and related modelling approaches.

b. This Scholarship is funded by the Australian Research Council (ARC) through the scheme Discovery Project (DP190101864).

2. Eligibility

a. The Scholarship is offered subject to the applicant having an unconditional offer of admission or being currently enrolled to study full-time in a research degree within the Faculty of Engineering at the University of Sydney.

b. Applicants must also hold at least an Honours degree (First Class or Second Class Upper) or equivalent in a relevant discipline.

c. Applicants must be willing to conduct research into integrated nano semiconductor devices and related modelling approaches.

3. Selection Criteria

a. The successful applicant will be awarded the Scholarship on the basis of:

I. academic merit, II. area of study and/or research proposal,

b. The successful applicant will be awarded the Scholarship on the nomination of the relevant research supervisor(s), or their nominated delegate(s).

a. The Scholarship will provide a stipend allowance of $33,000 (goal amount) for up to 11 months and it is maintained through satisfactory academic performance. No extension is possible.

b. The Scholarship is for commencement in the relevant research period in which it is offered and cannot be deferred or transferred to another area of research without prior approval.

c. No other amount is payable.

d. The Scholarship will be offered subject to the availability of funding.

5. Eligibility for Progression

a. Progression is subject to attending and passing the annual progress review.

6. Leave Arrangements

a. The Scholarship recipient receives up to 20 working days recreation leave each year of the Scholarship and this may be accrued. However, the student will forfeit any unused leave remaining when the Scholarship is terminated or complete. Recreation leave does not attract a leave loading and the lead supervisor's agreement must be obtained before leave is taken.

b. The Scholarship recipient may take up to 10 working days sick leave each year of the Scholarship and this may be accrued over the tenure of the Scholarship. Students with family responsibilities, caring for sick children or relatives, or experiencing domestic violence, may convert up to five days of their annual sick leave entitlement to carer’s leave on presentation of medical certificate(s). Students taking sick leave must inform their lead supervisor as soon as practicable.

7. Research Overseas

a. Scholarship recipients commencing in Australia may not normally conduct research overseas within the first six months of award.

b. Scholarship recipients commencing in Australia may conduct up to 12 months of their research outside Australia. Approval must be sought from the student's supervisor, Head of School and the Faculty via application to the Higher Degree by Research Administration Centre (HDRAC), and will only be granted if the research is essential for completion of the degree. All periods of overseas research are cumulative and will be counted towards a student's candidature. Students must remain enrolled full-time at the University and receive approval to count time away.

c. Scholarship recipients who are not able to travel to Australia to start their degree, may commence their studies overseas part-time. Approval must be sought from the student’s lead supervisor and will only be granted where a progress plan has been agreed and application for remote candidature has been approved by the Associate Dean (Research Education), or their nominee. Students commencing their degree overseas will receive this scholarship initially for 12 months. The stipend payment for the period spent overseas will be paid on a pro-rata basis and made when students arrive in Australia and is subject to confirmation of satisfactory progress from the lead supervisor. Extensions beyond 12 months, if scholarship recipients are not able to travel to Australia, will be considered on a case by case basis and subject to the approval of an application to extend their remote candidature.

8. Suspension

a. The Scholarship recipient cannot suspend their award within their first six months of study, unless a legislative provision applies.

b. The Scholarship recipient may apply for up to 12 months suspension of the Scholarship for any reason during the tenure of the Scholarship. Periods of Scholarship suspension are cumulative and failure to resume study after suspension will result in the award being terminated. Approval must be sought from the student's supervisor, Head of School and the Faculty via application to the Higher Degree by Research Administration Centre (HDRAC). Periods of study towards the degree during suspension of the Scholarship will be deducted from the maximum tenure of the Scholarship.

9. Changes in Enrolment

a. The Scholarship recipient must notify HDRAC, and their lead supervisor promptly of any planned changes to their enrolment including but not limited to: attendance pattern, suspension, leave of absence, withdrawal, course transfer, and candidature upgrade or downgrade. If the award holder does not provide notice of the changes identified above, the University may require repayment of any overpaid stipend.

10. Termination

a. The Scholarship will be terminated:

I. on resignation or withdrawal of the recipient from their research degree, II. upon submission of the thesis or at the end of the award, III. if the recipient ceases to be a full-time student and prior approval has not been obtained to hold the Scholarship on a part-time basis, IV. upon the recipient having completed the maximum candidature for their degree as per the University of Sydney (Higher Degree by Research) Rule 2011 Policy, V. if the recipient receives an alternative primary stipend scholarship. In such circumstances this Scholarship will be terminated in favour of the alternative stipend scholarship where it is of higher value, VI. if the recipient does not resume study at the end of a period of approved leave, or VII. If the recipient ceases to meet the eligibility requirements specified for this Scholarship, (other than during a period in which the Scholarship has been suspended or during a period of approved leave).

b. The Scholarship may also be terminated by the University before this time if, in the opinion of the University:

I. the course of study is not being carried out with competence and diligence or in accordance with the terms of this offer, II. the student fails to maintain satisfactory progress, III. the student has committed misconduct or other inappropriate conduct.

c. The Scholarship will be suspended throughout the duration of any enquiry/appeal process.

d. Once the Scholarship has been terminated, it will not be reinstated unless due to University error.

11. Misconduct

a. Where during the Scholarship a student engages in misconduct, or other inappropriate conduct (either during the Scholarship or in connection with the student’s application and eligibility for the Scholarship), which in the opinion of the University warrants recovery of funds provided, the University may require the student to repay payments made in connection with the Scholarship. Examples of such conduct include and without limitation; academic dishonesty, research misconduct within the meaning of the Research Code of Conduct 2023 (for example, plagiarism in proposing, carrying out or reporting the results of research, or failure to declare or manage a serious conflict of interests), breach of the Student Charter 2020 and misrepresentation in the application materials or other documentation associated with the Scholarship.

b. The University may require such repayment at any time during or after the Scholarship period. In addition, by accepting this Scholarship, the student consents to all aspects of any investigation into misconduct in connection with this Scholarship being disclosed by the University to the funding body and/or any relevant professional body.

12. Reports

a. The successful recipient of this Scholarship may be requested to contribute to the progress/ and final reports to ARC.

13. Intellectual Property a. The successful recipient of this Scholarship must complete the Student Deed Poll supplied by the University of Sydney

14. Publications

a. All ARC-funded research projects must comply with the ARC Open Access Policy on the dissemination of research findings, which is on the ARC website. In accordance with this

b. Any Research Outputs arising from ARC-funded research must be made openly accessible within a 12-month period from the publication date. Where this requirement cannot be met, reasons must be provided in the Final Report for the project.

c. The scholarship recipient will provide a copy of the proposed publication to each other Party at least 30 days in advance of submitting for publication. The other Parties may provide comments and/or reasonable amendments to the publication to protect their Confidential Information and/or Intellectual Property, including requesting removal or delay to the inclusion of information which may pre-empt the publication of their Project Intellectual Property, provided this is not jointly owned with the publishing Party. Any such comments and/or amendments must be given to the scholarship recipient in writing no later than 15 days before the publication is proposed to be submitted. If no such comments or amendments are provided within the 15-day period, the scholarship recipient can submit the proposed publication, subject to any applicable requirements under the Grant Agreement. Where a Party requests that the proposed publication be amended in accordance with this clause 5.5, the scholarship recipient will use all reasonable efforts to amend the proposed publication accordingly and, if requested, delay submission of the publication for a period not exceeding 6 months to allow appropriate registration of any registrable Intellectual Property.

15. Acknowledgements

a. The successful recipient agrees to include acknowledgement of the ARC’s funding, including the ARC project ID.

b. The successful recipient agrees that all Research outputs and metadata arising from the Project will be made available accessible in the timeframes and in accordance with the Grant Agreement.

c. The successful recipient agrees to acknowledge the ARC’s support in all Material, publications and promotional and advertising materials published in connection with this Agreement. The ARC will make available, on the ARC website, the form of acknowledgement that You are to use.

d. ARC’s contribution and support of the project is acknowledged in a prominent place and an appropriate form acceptable to the ARC when, at any time during or after completion of the project.

e. Where the Research Output is a publication, in addition to acknowledging ARC support, the relevant Project ID (DP190101864) must be included. Metadata for the Research Output must include the ARC Project ID, list the ARC as a Grant source and contain a permanent Digital Object Identifier (DOI) for the Research Output. If a DOI is not available, then a permanent Uniform Resource Locator (URL) link must be provided instead to the Research Output.

16. Confidentiality

a. The successful recipient agrees to not to disclose confidential information without prior written consent unless required or authorised by law or Parliament to disclose.  

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PhD projects

Several School members offer supervision for PhD research projects in the School of Mathematics and Statistics.

Navigate via the tabs below to view project offerings by School members in the areas of Applied Mathematics, Pure Mathematics and Statistics. (This list was updated September 2022.)

Please note that this is not an exhaustive list of all potential projects and supervisors available in the School. 

Information about PhD research offerings and potential supervisors can be found in various locations. It's worth browsing the current research students list to see what research our PhD students are currently working on, and with whom.

There is also a past research students list which provides links to the theses of former students and the names of their supervisors. 

It's also recommended to browse our Staff Directory , where our staff members' names are linked to their research profiles which provide details about their areas of research and often include the topics they are open to supervising students in.

We host PhD information sessions in the School of Mathematics and Statistics twice a year. Keep an eye on our events page for session information. 

• Applied mathematics
• Pure mathematics
• Real world problem solving using dynamical systems, stochastic modelling and queueing theory for stochastic transport and signalling in cells. 
• Real & Computational Algebraic Geometry: Possible subjects include nonnegativity of real polynomials, polynomial system solving, semialgebraic sets, and algorithmic aspects of real algebraic & convex geometry.
• Polynomial & Convex Optimization: Potential topics include convex relaxations, designing algorithms, exploiting structure (e.g. sparsity), and applications in science & engineering.
• Dynamical Systems and Ergodic Theory: Projects that combine techniques from nonlinear dynamics, ergodic theory, functional analysis, differential geometry, or machine learning and can range from pure mathematical theory through to numerical techniques and applications (including ocean/atmosphere/fluids/blood flow), depending on the student.
• Optimisation: Projects are occasionally available in optimisation, mainly using either techniques from mixed integer programming to solve applied problems (e.g. transport, medicine,…) or mathematical problems arising from dynamics.
• Modelling and analysis of ocean biogeochemical cycles including isotope dynamics, inverse modelling of hydrographic data to detect climate-driven circulation changes, and analysis of large-scale ocean transport. PhD students should be highly motivated, have a strong background in applied mathematics and/or theoretical physics, and will have the opportunity to contribute to shaping their project.
• Data-Driven Multi-stage Robust Optimization: The aim of this study is to develop mathematical principles for multi-stage robust optimization problems, which can identify true optimal solutions and can readily be validated by common computer algorithms, to design associated  data-driven numerical methods to locate these solutions and to provide an advanced optimization framework to solve a wide range of real-life optimization models of multi-stage technical decision-making under evolving uncertainty.
• Semi-algebraic Global Optimization: The goal of this study is to examine classes of semi-algebraic global optimization problems, where the constraints are defined by polynomial equations and inequalities. These problems have numerous locally best solutions that are not globally best. We develop mathematical principles and numerical methods which can identify and locate the globally best solutions.
• Detection and cloaking of surface water waves created by submerged objects
• Decomposition of ocean currents into wave-like and eddy-like components
• Theory and application of Quasi-Monte Carlo methods: for high dimensional integration, approximation, and related problems.
• Computational Mathematics: with specialised topics in radial basis functions, random fields, uncertainty quantification, partial differential equations on spheres and manifolds, stochastic partial differential equations. 
• Discrete Integrable Systems: These are birational maps with particularly ordered dynamics and their study is a nice motivation for using algebraic geometry, symmetry, ideal theory and number theory in the study of dynamical systems.
• Arithmetic Dynamics:  This field is the study of iterated rational maps over the integers or rationals or over finite fields, rather than the complex or real numbers. I am particularly interested in how the usual structures present in dynamical systems over the continuum manifest themselves over discrete spaces.
• Convex geometry: Focused on the study of the facial structure of convex sets and the relations between the geometry of convex optimisation problems and performance of numerical methods. The project can be oriented towards convex algebraic geometry, experimental mathematics or classical convex analysis.
• Algebraic and Geometric Aspects of Integrable Systems: The ubiquitous nature of integrable systems is reflected in their (apparent or disguised) presence in a wide range of areas in both mathematics and (mathematical) physics. Projects focus on the algebraic and/or geometric aspects of discrete and/or continuous integrable systems, depending on the individual student's background and preferences. 
• Analysis of multiscale problems in stochastic systems: These projects will involve an analytical study of certain multiscale problems arising in Markov chains and stochastic differential equations. These projects are suited for those interested in both analysis and probability, and will employ tools from differential equations, functional analysis and stochastic processes.
• Numerical methods for sampling constrained distributions: These projects are aimed at sampling problems arising in molecular dynamics. They will deal with designing and analysing numerical schemes to sample constrained probability distributions using stochastic differential equations.  
• Fluid flow in channels with porous walls
• Mathematics education
• Nonlinear differential equations
• Difference equations
• Dynamic equations on time scales
• How many oceans are there? Using novel statistical and machine learning techniques to characterise oceanic zones and provide a blueprint for quantifying the ocean's role in a changing climate.
• How does heat get into the ocean? An investigation of the physical mechanisms that control the ocean's uptake of heat and its effect on climate.
• Making climate models work better: Developing new methods to validate and improve the inner workings of numerical climate models and improve their projections of global warming and its impacts.
• Will it mix? New perspectives on turbulence in rotating fluid flows and how we estimate mixing from observations. 
• Combinatorics
• Graph theory
• Coding theory
• Extremal set theory
• Operator algebras (von Neumann algebras)
• Mathematical physics (quantum field theory)
• Group theory
• Jones subfactor theory
• Vaughan Jones' connection between conformal field theory, Richard Thompson's groups and knot theory.
• Noncommutative algebra
• Algebraic geometry
• Quantum groups/supergroups
• The Schur-Weyl duality
• Representation Theory
• Random graphs
• Asymptotic enumeration
• Randomized combinatorial algorithms

Extremal and probabilistic combinatorics: Possible subjects therein include Ramsey theory, random graphs, positional games and hypergraphs.

• Unlikely Intersection in Number Theory and Diophantine Geometry: These are problems of showing that arithmetic “correlations" between specialisations of algebraic functions are rare unless there is some obvious reason why they happen. These “correlations” may refer to common values or to values factored into essentially the same set of prime ideals and similar. 
• Arithmetic Dynamics: This area is concerned with algebraic and arithmetic aspects of iterations of rational functions over domains of number theoretic interest. 
• Isometries, conformal mappings, and other special mappings on metric Lie groups
• Complex structures on Lie groups and their Lie algebras
• Counting integral and rational solutions to Diophantine equations and congruences. The goal is to obtain upper bounds on the number of integer solutions to some multivariate equations and congruences in variables from a given interval [M, M+N]. Similarly, for rational solutions one restricts both numerators and denominators to certain intervals.
• Kloostermania: Kloosterman and Salie sums and their applications. A classical direction in analytic number theory where the goal is to obtain new bounds on bilinear sums of Kloosterman and Salie sums and apply them to various arithmetic problems, such as the Dirichlet divisor problem in progressions.

Exponential sums and applications. This topic is about understanding the behaviour (e.g. extreme and typical values) of some most important exponential sums, in particular of Weyl sums.  

• Non-commutative functional analysis and its applications to non-commutative geometry, particularly those related to quantised calculus and index theorems.
• Singular (Dixmier) traces and their applications
• Non-commutative integration theory
• Non-commutative probability theory
• Various aspects of Banach space geometry and its applications
• Algebraic geometry (birational geometry and moduli)
• Hodge theory
• Transcendental methods in algebraic geometry 
• Motivic cohomology and algebraic K-theory - an intersection of algebraic geometry and algebraic topology
• Equivariant algebraic topology
• Extreme Value Analysis: Projects available on the modelling of the dependence of multivariate and spatial extremes, spatio-temporal modelling, high-dimensional inference. Interests in environmental/climate applications. 
• Symbolic Data Analysis: Projects available on symbol design, distributional symbols and others. Applications in big and complex data analysis.
• Ancient river systems and landscape dynamics with Bayeslands framework
• Bayesian inference and machine learning for reef modelling 
• Deep learning for the reconstruction of 3D ore-bodies for mineral exploration 
• Bayesian deep learning for protein function detection  
• COVID-19 modelling with deep learning
• Variational Bayes for surrogate assisted deep learning
• Bayesian deep learning for incomplete information
• Computational Statistics
• Event sequence data analysis
• Hidden Markov Models and State-Space Models and their inference and applications
• Financial data analysis and modelling
• Point processes and their inference and applications
• Semi- and non-parametric inference
• Bayesian statistical inference
• Computational statistics and algorithms
• Approximate Bayesian inference
• Quantile regression method
• Statistical text analyses
• Applications to climate science, social science, image analyses

*Yanan Fan is an Adjunct A/Prof in the School and is able to co-supervise students (not as primary supervisor)

• Nonparametric and semiparametric statistics: Nonparametric dependence modelling (copulas) and nonparametric functional data analysis.
• Social network analysis for epidemiology, social sciences, defence, national security, and other areas
• Statistical models for dependent categorical data
• Survey sampling (design and inference), particularly for network data
• Statistical computing, particularly MCMC-based methods
• Dependence measures
• Complex-valued random variables
• Goodness-of-fit tests
• Machine learning (with potential applications in medical imaging)
• Time series analysis
• Real-time analytics with the Raspberry Pi
• For some examples of my current projects, have a look at my  personal webpage .
• Fast and efficient model selection for high-dimensional data
• Development of efficient estimation and sampling algorithms for random graphs and spatial point processes
• Development of model compression methods for deep neural networks.

Topics include regression to the mean, interrupted time series, meta-analysis, and population attributable fractions.

Monte Carlo and Uncertainty Quantification 

• Projects on the stochastic analysis and development of modern Monte Carlo methods for uncertainty quantification, sequential Bayesian inference, high dimensional sampling, particle based Variational Inference (knowledge/experience with stochastic analysis and SDE & PDE theory highly desired).

Machine learning and generative modelling 

• Projects with a focus on (but not restricted to) medical imaging and machine learning methods for uncertainty quantification of image segmentation
• Theoretical analysis of modern machine learning methods (knowledge/experience with functional and stochastic analysis highly desired).

Mathematics of sustainability 

• Projects on stochastic games, agent based models, network science and their applications in sustainability science.
• Automating data analyses via natural language queries
• Bayesian statistics, algorithms and applications
• Building software tools, services and packages
• Data privacy and synthetic data
• Data science, theory and application
• Defence applications (nationality restrictions may apply)
• Extreme value theory and applications
• Machine learning 
• Symbolic data analysis
• Developing statistical methods for point processes
• Financial data modeling
• Computational statistics
• Analysis of capture-recapture data
• Estimation of animal abundance
• Measurement error modelling
• Model selection for multivariate data
• Non-parametric smoothing
• Statistical ecology
• High-dimensional data analysis
• Simulation-based inference
• Eco-Stats project ideas

Potential PhD projects and scholarships

Potential PhD topics:

 1. What ocean do Lagrangian observing platforms (e.g., Argo and drifting buoys) observe ?

In the mid- and high-latitudes the ocean circulation is composed largely of eddies and fronts. In isolation an ocean eddy is relatively stable being in quasi-geostrophic balance and retaining a closed material surface around its core water mass. It is only through the disruption or destruction of this balance through eddy- interactions that an exchange in mass with its environment takes place. Only at these times is it possible for a Lagrangian observing platform to enter or exit the eddy circulation. This poses many interesting questions such as how frequently do these platforms observe eddies and what are the implications for constructing climatologies of the ocean and ocean forecasting. This research would make use of state of the art high resolution ocean models, analysis of altimetry and the in situ Argo and drifting buoy observations available at the Bureau of Meteorology and the global ocean observing system.

2. Characterisation of ocean forecast errors from an ocean forecasting system . A state-of-the-art prediction system makes several assumptions about the errors of the observing system, the ocean models, the atmospheric forcing and data assimilation methodology. Correctly modelling and estimating these errors and validating or improving these assumptions is critical to further improving performance. This project will focus on the available database of forecast innovations and increments from the BLUElink ocean prediction system and determine the systematic bias as well as the statistical distribution. Specific methods will then be developed to deconstruct and attribute error to different components of the system as well as hypothesis testing.

3.  Helen Beggs leads the  GHRSST Tropical Warm Pool Diurnal Variability (TWP+) Project  which aims to quantify diurnal warming of the surface ocean over the Tropical Warm Pool to the north of Australia and to validate and compare various diurnal variation models over this region.

The  International Group for High Resolution Sea Surface Temperature (GHRSST) TWP+ data set  would be a great resource for any PhD student with a background in either physical oceanography, air-sea heat exchange, marine meteorology and/or satellite oceanography. Further information on the TWP+ Project can be found at  https://www.ghrsst.org/ghrsst-science/science-team-groups/dv-wg/twp/  < https://www.ghrsst.org/ghrsst-science/science-team-groups/dv-wg/twp/>  .

The  GHRSST Workshop on Tropical Warm Pool and High Latitude SST Issues  (Melbourne, 5-9 March 2012) would be an excellent opportunity for a new PhD student to choose a TWP+ related research project that matches their interests and abilities. The workshop will focus on presentations relating to initial research for the TWP+ Project and using the TWP+ data set during the three working days of the GHRSST workshop. Further information on the GHRSST Workshop can be found at  https://www.ghrsst.org/ghrsst-science/Meetings-and-workshops/workshop-on...  < https://www.ghrsst.org/ghrsst-science/Meetings-and-workshops/workshop-on...  including a draft agenda which lists the current TWP+ research activities.

4. Impact of East Australian Current observations Tasman Sea eddies in an ocean model

Introduction

Can observations of the East Australian Current using a HF ocean surface radar improve model forecast skill of meso-scale eddies in the Tasman Sea?

The study will use observations at Coffs Harbour (30S, 153E) which extend approximately 100 km east across the East Australian Current (EAC) and perform assimilation impact studies on a domain encompassing upstream of Coffs Harbour, the EAC separation (at approximately Smoky Cape, 31 S), and the Tasman front (across to New Zealand), with a particular emphasis on meso-scale eddies.

OSR observations

The HF OSR measures surface currents in the top few tens of centimetres of the ocean, on a few km resolution with a range of around 100km over 10 minute time scales. The OSR is part of the IMOS ACORN facility and is planned to commence operation in February 2012. Routine data delivery could be expected by mid 2012. Observations show the EAC is largely barotropic, so OSR should be representative of the depth-integrated current.

The Ocean Model CLAM? Assimiliation

The HF OSR provides currents in regions where the two radars overlap (and the subtended angles of the ray are greater than ~20 Outside of this region there is another equally extensive area where there is only one useful current vector component resolved. While not suited to visual interpretation, single current vector components can be assimilated into ocean models.

The model already assimilates altimetry, SST and temperature and salinity profiles, so any skill improvement will be in excess of this. The assimilation of HF OSR observations may also be useful in the situation where altimetry is degraded (due to loss of satellites or other problems). It would be useful to quantify the impact of assimilating OSR currents in the absence (or reduction) of altimetry.

Possible candidate data-sets for skill evaluation are feature tracking, surface drifters (these are probably drogue to a few metres depth), or synTS. The first two sources will probably generate sparse data-sets. Maybe the evaluation will be achieved by looking at the increments in SSH?

Links to other Work

We have previously looked at the impact of observations on models using the error estimates in the data assimilation system (Oke  et al. , 2009). It would be instructive to see how data withholding experiments compare to the observation network design study tool.

Oke, P. R., Sakov, P. & Schulz, E.W., 2009, A comparison of shelf observation platforms for assimilation in an eddy-resolving ocean model,  Dynamics of Atmospheres and Oceans,  48, 121-142, doi:10.1016/j.dynatmoce.2009.04.002.

5. Predictive mapping of seabed cover, benthic habitats, benthic biodiversity using multibeam bathymetry and backscatter data

Coastal marine benthic environment, which is dreadfully under-studied, has significant economic and conservation values. Sustainable management of this marine ecosystem requires high quality physical and biological datasets on the benthic environment and scientific evidence on the interactions between these physical and the biological variables. Modern mutlibeam sonar systems, with different sonar frequencies, are capable of accurately mapping large area of seabed from water depth of a few metres to thousands metres. They can provide high-resolution and near-complete coverage of bathymetry and acoustic backscatter data for mapping seabed substrata, benthic habitats and benthic biota.

The proposed project would involve intensive field campaigns collecting multibeam data, water column data, sediment samples and biological data. The collaboration with OUC is critical for the collection and analysis of these data. We would provide expertise in the areas of data analysis, modelling and result interpretation.

6. Generalised dependence for the ocean sea drag

The sea--‐drag coefficient is the main property which is employed to parameterise the air--‐sea interactions in large--‐scale models, from engineering applications to climate research. Over the last 30 years, however, scatter of the experimental dependences for the sea drag parameterised as a function of wind speed and/or wave age did not improve. The proposed project would intend to develop a generalised parameterisation of the sea drag as a function of multiple environmental forcings, for use in meteorological, climate and ocean engineering applications.

7. Coastally trapped wave observations and modelling around Australia

Program Code: 1082

Supervisors:  Prof. Xiao Hua Wang ( [email protected] ), Dr Ming Feng, CSIRO, A/Prof Moninya Roughan and Dr Andrew Kiss (UNSW)

Australia is surrounded by major ocean boundary currents – with the East Australian Current off the east coast, the Leeuwin Current off the west coast, and the South Australian Current/Flinders Current off the south coast. The Integrated Marine Observing System (IMOS) has set up shelf circulation monitoring systems for the major boundary current systems over the past six years. The observing systems include shelf moorings, gliders, and surface radar systems. The ocean boundary current systems vary on different time scales, such as seasonal and intra-seasonal. The aim of this study is to utilise the IMOS mooring networks and numerical models to understand the coastally trapped wave propagations around Australia, forced by wind anomalies on intra-seasonal and whether time scales, and their interactions with the ocean boundary current systems. The intra-seasonal variability of the ocean boundary currents are important in understanding the extreme events in these systems.

8. Remote sensing study on the East Australian Current

Supervisors:  Prof. Xiao Hua Wang ( [email protected] ) and Dr Zhi Huang, Geoscience Australia

East Australian Current (EAC) is a significant boundary current that flows poleward. On the way, it separates and generates many large and small eddies that cause lots of oceanographic dynamic. It has significant ecological impact on the eastern margin of Australia from about 25S. This PhD project aims to use time-series remotely sensed data to map EAC’s spatial structures and investigate the spatial and temporal variability of EAC’s characteristics. The remotely sensed data to be used include more than 10 years MODIS SST and Chlorophyll a datasets. We also intend to use satellite altimetry data in combination with the broad scale BlueLink model to help the mapping and validation, especially in the identification of eddies. This PhD project will further develop the techniques used in supervisor’s (Huang) similar study on the Leeuwin Current of Western Australian margin (Huang and Feng, 2015). Co-supervisor Wang’s expertise in EAC system will be utilised in guiding the design of this study and assessing the results of this study, among others. The successful PhD candidate is expected to have a strong research and analytical skills. Experience and skills in either Remote Sensing or Physical Oceanography field or both are highly desirable.

9.  Mapping and modelling the coastal upwelling along NSW

Supervisors:  Dr Zhi Huang and Prof. Xiao Hua Wang ( [email protected] ), Geoscience Australia

Coastal upwelling is important for marine ecosystems and the economy, because of its elevated primary and secondary productivity and large potential for fish catch. Upwelling along the New South Wales (NSW) coastal areas forms a prominent upwelling system. The upwelling system occurs more or less continuously from austral spring to autumn. It is believed that the East Australian Current (EAC) plays a critical role in this upwelling system.

The ability to investigate the development of individual upwelling events became available in recent years since the production of highly frequent remotely sensed SST data. The Himawari-8 (H-8) is a new generation geostationary satellite carrying an Advanced Himawari Imager (AHI), capable of providing geophysical data at a spatial resolution of 2km and a temporal resolution of 10-mins full-disk frequency. This PhD project contains two main stages. Firstly, this project uses the H-8 SST data to identify and explicitly map the development of individual upwelling events along the NSW coast. The project then uses numerical ocean model(s) to simulate the development of these events to investigate the major underlying mechanisms. The results of this PhD research would significantly advance our knowledge on the NSW coastal upwelling system which is likely to be increasingly influenced by the climate change.

These brief research questions are possible projects for research higher degree students under the supervision of A/Prof.   Stuart Pearson .

• What is the Blue Economic Zone and what will its success bring to society, environment and economy? How will it be monitored and evaluated? What does this show about the research needs for China’s environmental law, science and management? [with A/Prof Ma Yingjie]
• Why is eco-compensation so popular in China? What does this show about the research needs for China’s environmental law, science and management? [with Ma Yingjie]
• How is risk of environmental research, environmental management and environmental policy considered in Australia and China? Current topics for PhDs have related to biofuel policy [with Dong Bo], Antarctica’s research program [with Maozeng Jiang] and so what do you think should be studied next?
• Who cares?  Using a social science approach, how can the values, attitudes and dreams of Australia and China’s young professionals be understood and what scenarios can be plausibly developed? Environmental research, environmental management and environmental policy considerations of young people in Australia and China. How does this contribute to government research? [with Yantai Institute and NSW Government]
• How widely and how appropriate is applying the Kuznets curve thinking in China a rational Natural Resource Management response? China’s rapid development and transition to a eco-civilisation is widely discussed as a stage requiring ‘development first and clean-up second’. What is the nature of the evidence used by narrators to justify this and what are the plausible scenarios?

Climate change implications for Estuaries

Climate variation and change will impact estuaries in a manner and to a degree that is presently poorly understood due to the uncertainties regarding future forcing and theoretical impediments to our quantitative understanding of estuarine processes at management timescales. Estuarine habitats, water quality, shoreline stability, long-term sedimentation, groundwater, freshwater management as well as the inundation of adjacent land and built environment will all potentially be significantly impacted by climate change.

The purpose of this project is to determine likely changes in forcing processes and extreme events (floods, droughts, heat waves, coastal storms) on Australian estuarine ecosystems and their future management.

Specific questions that will be addressed are as follows:

How are estuarine ecosystems anticipated to change with climate?

What options can be exercised to address these changes within estuaries and their catchments?

What appropriate strategies can be exercised to minimise ecological, social and financial risk in estuarine systems?

This project would be supervised in collaboration with suitably qualified ecologists.

Geomorphological behaviour of estuaries under climate change

Estuarine geomorphological behaviour and its response to physical modification and bioturbation provides the physical backdrop for estuary change. A contemporary need is to integrate science and engineering approaches to understand estuaries on a range of nested time scales: the storm event cycle; interannual climate variability; multi-decadal climate variability; centennial to millennial sedimentological and geomorphological processes.

Specifically, marine and terrestrial sedimentation determines the rate of estuarine infilling and changes in estuarine form according to its maturity (Roy  et al ., 2001, Structure and Function of South-east Australian Estuaries,  Estuarine, Coastal and Shelf Science ,  53 ). Floods play a major role in infilling, flood plain sedimentation as well as scouring during major events.

Following a review of the role of time scale in estuary development, detailed assessment of selected sites would be undertaken as case studies.

PhD Scholarships for International Students from UNSW Canberra

UNSW Canberra will provide a living stipend valued at $35,000 per annum for 3.5 years for suitably qualified students.

INFORMATION ON SCHOLARSHIPS:  www.unsw.adfa.edu.au/hdr-scholarships

UNSW Sydney NSW 2052 Australia Telephone +61 2 93851000 Authorised by Deputy Vice-Chancellor (Research) UNSW CRICOS Provider Code: 00098G ABN: 57 195 873 179

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PhD and research degrees

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