Promotion in Ingenieurswissenschaften, Informationstechnologie und Computer Sciences

This PhD is an exciting opportunity for a highly motivated candidate who wants to see their research translated into clinical practice and directly benefit patients. The project aims to develop personalised models of patients' pre- and post-Percutaneous Coronary Intervention (PCI) with stents.

During the course of this PhD, the successful candidate will attain the required ethical approval and collect patient-specific imaging data before running a range of computational and experimental tests.

The right candidate will work closely with a multi-disciplinary team across medicine, computer sciences and mechanical engineering. Relevant previous research experience is desired. The right candidate must be an experienced ANSYS fluid dynamic user or similar and have a good fluid dynamic understanding in the biomedical engineering context. 

Strong problem-solving skills, motivation and good communication skills are required. An interest in and willingness to learn about cardiovascular disease is critical. Previous experience in publishing is highly desirable.

You will be part of an international, dynamic, and thriving team based in Sydney, Australia, which values teamwork, inclusivity, and excellence. Weekly group and individual meetings will allow you to excel in your work. For more details, please see www.svmgroup.org. 

Female applicants are highly encouraged. 

This PhD project aims to develop a new method to purify silk proteins using liquid chromatography. If successful, it could create a new class of “chromatographically degummed” silk proteins. It will study the properties and interactions of these extracted proteins compared with conventionally processed silk. The project is only possible thanks to a recent breakthrough made by the Deakin silk research team, which developed a new method to re-solubilise silk fibres.

If successful, this could lead to next generation silk-based materials with outstanding mechanical properties. Understanding the properties of the extracted proteins in their undegraded state will also help to answer key questions about how silkworms can spin fibres at room temperature with properties that rival many synthetic fibres. The project will also explore the properties of sericin extracted using a newly developed extraction method. This sericin will be explored for applications such as 3D printing or to develop injectable hydrogels.

Silkworm silk is a remarkable material; in addition to its use in high end textiles, it has been explored for applications ranging from regenerative medicine, drug delivery, cosmetics and even as edible coatings to preserve fruit and vegetables. To use silk for such applications it must first be “degummed” to remove sericin, the glue that holds the cocoon together. Despite decades of research, the most used degumming method involves boiling cocoons in an alkaline bath to dissolve sericin. This process is damaging to the remaining silk fibres, compromising their mechanical properties and changing silk’s properties in solution completely.

This scholarship is available over three years and offers:

• a stipend of $37,450 per annum tax exempt (2026 rate)

For international students, the awardee will also receive:

• tuition fees offset for the duration of four years
• single Overseas Student Health Cover policy for the duration of the student visa.

Additional desirable criteria include:

• a background in chemistry, biology or materials science; experience in protein biochemistry is highly desirable.

Heart valves often become weak with old age, previously a common cause of death. Open heart surgery has been too invasive in the past. However, a new minimally invasive procedure (called TAVI) has now made this intervention safer and more accessible, helping many affected patients worldwide live longer, better quality lives.

Still, the success of the surgery largely depends on the quality of the medical imaging during the implant of the new value, which is 2D, greyscale and often has a poor spatial and temporal resolution. Immersive technologies such as AR and VR have rapidly emerged in recent years, but their translation into the surgery room remains fictional.

This PhD will explore how AR and VR technology can be integrated as tools to assist live surgical TAVI procedures. The ideal candidate has a strong programming background and experience with immersive technologies. Strong problem-solving skills, motivation and good communication, and a passion for health technologies are required.

This interdisciplinary PhD is an excellent opportunity for a postgraduate student to pursue world-leading and novel research of significant translational impact, offering various career paths and stimulating intellectual challenges. 

The project will bring together leading experts from creative technologies, engineering and medicine as a supervisory and advisory team as part of an international, dynamic, and thriving team based in Sydney, Australia. We value collaboration, inclusivity, and excellence. Weekly group and individual meetings will allow you to excel in your work. For more details, please see www.svmgroup.org.

 Female applicants are highly encouraged. 

Artificial reefs are increasingly being deployed along coastlines worldwide for a range of purposes, including recreation, habitat enhancement and coastal management. While numerical and physical modelling are commonly used to inform reef design and approvals, there remains limited quantitative, field‑based evidence evaluating how artificial reefs interact with nearshore hydrodynamics, sediment transport and beach evolution once constructed, particularly in high‑energy wave environments.

A central motivation for this project is the need to empirically assess post‑construction coastal response to artificial reefs, and to evaluate assumptions commonly made during the design and approval process. By resolving coastal processes across a range of temporal and spatial scales, the project will improve understanding of how reef geometry, placement and wave climate influence coastal behaviour.

This project will investigate the coastal impacts of artificial reefs, with a focus on understanding how engineered reef structures modify wave transformation, nearshore circulation, sediment transport pathways and shoreline response. The research will address key knowledge gaps related to whether, and under what conditions, artificial reefs produce measurable changes to beach morphology, erosion and accretion patterns, or nearshore sediment dynamics.

The project will employ a combination of field‑based observations (e.g. wave and current measurements, beach and seabed surveys, sediment monitoring) and remote‑sensing and data‑driven analyses (e.g. satellite imagery, UAV surveys, coastal monitoring datasets). Outcomes will provide robust, evidence‑based insights to inform the design, monitoring and management of artificial reefs in energetic coastal environments. 

Read more about the project here.

Applicants will be required to apply for available scholarship opportunities. 

Any fully-funded scholarship opportunities will be linked to this project opporutnity via HDRhub. 

Laser signals (visible and infrared light) can support data transfer at rates orders of magnitude higher than conventional radio frequency (RF) signals. That is why the majority of internet traffic travels as laser light through optical fibre networks rather than electrical signals through copper wire. Wireless communications, however, have remained in the realm of RF due to the challenges of free-space laser communications. This is a problem as the RF spectrum is a finite resource and has reached its practical limit. We are working to overcome these challenges, developing optical terminals for laser links between moving vehicles, as well constructing the TeraNet optical ground station network to support ground-to-space laser communications that will break the data transfer bottleneck imposed on spacecraft operators.

Topics include:

• Optical Ground Station Network Automation and Optimisation — A major weakness in laser communications is weather; lasers cannot propagate through clouds. The way around this is to use multiple optical ground stations (OGS) that overlap in their coverage but are far enough apart that the weather they experience is not correlated. This project would investigate how an OGS network can be automated and optimised.
• Atmospheric Mitigation — Atmospheric turbulence degrades an optical signal, reducing its capacity to transmit data. Adaptive optics (AO) is a mature technology used by astronomers to correct for this, but optical ground stations will need to operate under less favourable conditions than the pristine sites that astronomical observatories are located. This project would investigate various turbulence mitigation strategies for laser communications.
• Mobile Terrestrial Laser Communications — Laser communications can also be employed in terrestrial scenarios where high bandwidth and/or secure communications are needed, but optical fibre is impractical. This project would involve the design and implementation of optical terminals that could be vehicle-mounted and operate over links of ~20km. 

Read more about the project here.

The Australian Government’s Research Training Program (RTP) provides funding to support both domestic and international students undertaking Research Doctorate and Research Master’s degrees. At UWA, RTP funding is used to support eligible students through the following types of scholarships:

International RTP Tuition Fees Offset Scholarships - awarded to a limited number of international students, via a competitive selection process.

RTP Stipend Scholarships (living allowance) - awarded to a limited number of domestic and international students, via a competitive selection process. The current value in 2026 is $38,110 per annum.

RTP Allowances - awarded to assist students with ancillary costs of Higher Degree by Research, such as relocation expenses.

The unprecedented accuracy and stability of frequency references created by optical atomic clocks could form the backbone of next-generation quantum-limited optical-frequency positioning, navigation and timing networks.However, this requires correspondingly stable techniques for transmitting optical reference signals over atmospheric channels between locations of interest. Transmission of these optical signals comes with significant challenges, including: disruption by atmospheric turbulence; high Doppler shifts; and extreme power losses over long distances. Our research team has pioneered a technique that relies on the transmission of a continuous-wave optical carrier with active phase compensation to transfer the frequency reference in a stable manner.

PhD topics include:

• Weak light phase tracking through atmospheric turbulence: Free-space optical frequency transfer is always limited by the link-losses associated with atmospheric propagation. This project will look into the fundamental limits of frequency transfer at the quantum limit in the presence of significant scintillation.
• High-precision frequency transfer over highly dynamic atmospheric links:  Doppler frequency shifts over atmospheric links, particularly within ground-to-space contexts, significantly exacerbate the difficulties associated with optical frequency transfer.

We are looking for a dedicated and enthusiastic student willing to learn from and collaborate with a team of optical researchers and physicists in the Astrophotonics Group (www.icrar.org/astrophotonics). The student will be given the opportunity to work in a world-class optical laboratory and to develop skills relevant to optical engineering, experimental physics and the budding Australian space industry. Additionally, this work will be conducted in collaboration with research groups from across Australia and around the world.

Read more about the project here.

The Australian Government’s Research Training Program (RTP) provides funding to support both domestic and international students undertaking Research Doctorate and Research Master’s degrees. At UWA, RTP funding is used to support eligible students through the following types of scholarships:

International RTP Tuition Fees Offset Scholarships - awarded to a limited number of international students, via a competitive selection process.

RTP Stipend Scholarships (living allowance) - awarded to a limited number of domestic and international students, via a competitive selection process. The current value in 2026 is $38,110 per annum.

RTP Allowances - awarded to assist students with ancillary costs of Higher Degree by Research, such as relocation expenses.

Radio telescopes such as the ngVLA and SKA phase-2 will allow astronomers to study the universe with 100 times greater depth and resolution than ever before, enabling discoveries that will shed light on mysteries ranging from the beginning and evolution of the universe, to the origin of life on Earth. To do this, hundreds of radio dishes need to be synchronised with extreme accuracy and precision. The Astrophotonics Group (www.icrar.org/astrophotonics) at the International Centre for Radio Astronomy Research (ICRAR) developed the current frequency synchronisation systems for SKA phase-1, which is currently being manufactured. 

Several project themes are on offer including, PhD topics include:

• Frequency dissemination and phase stabilisation system — Building on the SKA Frequency distribution system currently being manufactured by UWA, the student will help design, build, and test an FPGA-controlled, optical fibre-based time and frequency distribution system tailored to the scientific needs and engineering challenges of next generation telescope arrays, e.g., the ngVLA and SKA phase-2. The system will use digital signal processing (DSP) on an FPGA to modulate, receive, and stabilise time and frequency signals transmitted over hundreds of kilometres of optical fibre.
• Giving back to metrology — with the SKA phase-1 frequency distribution system currently being manufactured by UWA, a phase jitter performance of 40 fs is achieved. Redefining this system to be implemented for metrology or relativistic geodesy purposes could significantly advance these fields. This work will extend on the SKA work performed and redefine the system for implementation in large-scale
• Fast imaging backend — enhanced radio astronomy widefield imaging efficiency through the use of in-hardware parallelisation using Fast Spherical Harmonic Transforms. This approach significantly reduces the data cost of converting voltages to widefield accurate snapshot images. Synthesis will be performed on FPGA hardware interfaced with fibre-optic backend (RFoF) to mitigate cable losses.

Read more about the project here.

The Australian Government’s Research Training Program (RTP) provides funding to support both domestic and international students undertaking Research Doctorate and Research Master’s degrees. At UWA, RTP funding is used to support eligible students through the following types of scholarships:

International RTP Tuition Fees Offset Scholarships - awarded to a limited number of international students, via a competitive selection process.

RTP Stipend Scholarships (living allowance) - awarded to a limited number of domestic and international students, via a competitive selection process. The current value in 2026 is $38,110 per annum.

RTP Allowances - awarded to assist students with ancillary costs of Higher Degree by Research, such as relocation expenses.

This is an opportunity for a PhD in a rapidly growing area in Machine Learning. Spiking neural networks (SNNs) much more closely mimic the operation of a real brain than traditional artificial neural networks (ANNs) by reproducing the spike-driven nature of real neurons. There is also the opportunity to collaborate with SynSense AG, a startup developing neuromorphic hardware to execute SNNs at low power.

While most simulations of spiking neurons networks (SNN) are conducted with 32-bit floating point precision, digital spiking neuron hardware often operates with quantised integer logic, at reduced bit depths.

SNNs have several computational requirements for spiking neurons, which should be aligned with efficient hardware implementation. The first is simulation or approximation of exponential decay, to support synaptic and membrane dynamics. Accuracy here is required to ensure compatible dynamics between floating-point simulations and hardware implementation. A HW numerical representation that makes exponential decay both cheap and accurate would be highly desirable.

The second is a requirement for accurate representation of numbers close to threshold. Whether or not a neuron crosses threshold has a large impact on the performance and behaviour of a spiking network. We suggest an exploration of whether concentrating the numerical representation around threshold (e.g. around 1.0) provides benefits to network accuracy or simulation accuracy in the face of reduced bit-depth.  

Read more about the project here.

The Australian Government’s Research Training Program (RTP) provides funding to support both domestic and international students undertaking Research Doctorate and Research Master’s degrees. At UWA, RTP funding is used to support eligible students through the following types of scholarships:

International RTP Tuition Fees Offset Scholarships - awarded to a limited number of international students, via a competitive selection process.

RTP Stipend Scholarships (living allowance) - awarded to a limited number of domestic and international students, via a competitive selection process. The current value in 2026 is $38,110 per annum.

RTP Allowances - awarded to assist students with ancillary costs of Higher Degree by Research, such as relocation expenses.

The ideal candidate will hold either a Mathematics, Computer Science or Electronic Engineering Bachelor Honours or Masters degree with some experience in computational methods and design for embedded hardware.

Skills

• Python
• Machine Learning optimisation. Experience with DNN training is desirable 
• Low-level HDL coding
• Knowledge of numerical representations is desirable

Training and Development

The candidate will be responsible for designing and evaluating numerical representations, in the context of SW and HW simulations of spiking neurons. Potential collaborations with SynSense, a commercial neuromorphic processor hardware startup, are available.  

Science is becoming increasingly data intensive and this requires a new data focused approach. The prime example is the Square Kilometre Array (SKA) project, one of the world’s latest large-scale global scientific endeavours, which will be co-hosted in Australia and is set to produce orders of magnitude more data than all of mankind’s past accomplishments. Just one of the SKA phase-1 science projects (e.g. the HI survey) will produce derived data in the order of several terabytes per second, and the second phase of the SKA project will be at least an order of magnitude greater.The project

This project in Data Intensive Astronomy will bridge the computer science-focused data-driven approach to the science applications. Data Intensive Science has become fundamental to deliver any modern-day cutting edge science, and this position bridges the technical issues and the astronomical requirements. The PhD projects will provide engagement with industry and other partners and a unique training environment, working at the cutting edge of radio astronomy, computer science and commercial business and scientific systems.

The Computer Science element will cover: profiling basic algorithms to measure various compute metrics and creating data slicing helper functions based on information derived from measured metrics; characterisation of the transitions between compute intense and I/O intense phases, the balancing of these being central to getting the best performance. Supervision will primarily be by Prof. Wicenec.

The practical aspect will be to work on some of the most extreme datasets observed in Radio Astronomy to date, which will provide a perfect test bed for the data-driven paradigm. The data we will use will come from the Australian SKA Pathfinder project, DINGO. The student will investigate the ideas and methods, demonstrating new approaches on frontier data products. Supervision will primarily be by Dr. Dodson.

Read more about the project here.

The Australian Government’s Research Training Program (RTP) provides funding to support both domestic and international students undertaking Research Doctorate and Research Master’s degrees. At UWA, RTP funding is used to support eligible students through the following types of scholarships:

International RTP Tuition Fees Offset Scholarships - awarded to a limited number of international students, via a competitive selection process.

RTP Stipend Scholarships (living allowance) - awarded to a limited number of domestic and international students, via a competitive selection process. The current value in 2026 is $38,110 per annum.

RTP Allowances - awarded to assist students with ancillary costs of Higher Degree by Research, such as relocation expenses.

This PhD is an exciting opportunity for a highly motivated candidate with academic ambitions. The project aims to develop a new suit of biofluids solver as a significant advance for medical diagnostics and device development.

During this PhD the successful candidate will develop physics-informed neural networks to accurately predict fluid dynamics in large generalised vascular networks such as the coronary artery tree or the Circle of Willis.

The right candidate will work closely with a multi-disciplinary team across medicine, computer sciences and mechanical engineering. Relevant previous research experience is desired. The right candidate must be an experienced Python user and should have worked with neural networks before. A good fluid dynamic understanding, especially for biological systems, and a strong mathematical understanding are preferable. 

The continuous increase in energy conversion efficiency and decrease in cost have made solar power the cheapest form of electricity in most countries. As a result, silicon-based solar cell technologies are dominating the global photovoltaic (PV) market. However, as the efficiency of silicon single junction solar cells approaches its theoretical limit, the PV industry and research community are turning their attention to next-generation technologies like tandem solar cells. Tandem solar cells use multiple layers of light-absorbing materials with different bandgaps to better utilise the solar spectrum, making them more efficient than single-junction cells. While tandem solar cells are an exciting new technology, they still require intensive research to become commercially viable.

Characterisation plays a vital role in the development of solar cells. Note that the world record for silicon solar cell efficiency that had been held by UNSW for many decades was strongly supported by the availability of state-of-the-art characterisation tools. In this project, we are seeking a motivated PhD candidate to develop advanced characterisation techniques for tandem solar cells to bring transformative change to the PV industry. More specifically, you will develop:

Advanced in-depth characterisation techniques to better understand the material properties and device physics of tandem solar cells, assisting the optimisation of tandem solar cells.
High throughput quality-inspection techniques to facilitate the mass production of tandem solar cells.
You will explore multiple advanced characterisation techniques including Kelvin probe, magnetic field imaging, hyperspectral imaging, and many more. You will also innovatively adapt several existing characterisation techniques for single junction solar cells to tandem solar cells, such as luminescence imaging, time-resolved photoluminescence, etc. Through a collaborative environment, you will get access to state-of-the-art laboratories, high efficiency tandem solar cells, as well as industrial large area devices. Apart from hands-on experience during the developing of novel characterisation systems, you will also gain knowledge and skills in simulation and loss analysis of tandem solar cells. 

$37,684 per annum (2024 rate, indexed) for 3.5 years. International candidates will receive a tuition fee scholarship.

Commercial maturity of Power-to-X (P2X) technologies to utilise renewable energy resources for electrochemical conversion of abundant molecules like water, CO2, and N2, into green renewable energy-carriers, fuels and chemical feedstocks have opened new avenues for deep-routed decarbonisation. A transition that is well underway, with 25 of the world’s largest and leading economies introducing policies and incentives to kick start the P2X economies, leading to large scale up of electrolyser manufacturing, renewable energy deployment for P2X and a commitment of investment of ~240 billion USD.

Yet only 4 - 10% of these investment commitments have reached a final investment decision (FID). The critical bottlenecks are the current high cost of electrolysis technology, renewable electricity, and low capital efficiency of the projects due to intermittent and variable operation of solar/wind energy sources which results in high production costs making them unviable against their fossil fuel counterparts. However, there is expectation that the cost of P2X will decrease with ongoing cost reduction in electrolyser and renewable energy production, achievement of economies of scale and optimisation of project designs. Therefore, in the meantime while the cost remain high and relatively incompetent for large scale offtake, there is a need to find niche utilisation opportunities to enable scale up of technology.

This PhD project will focus on the technoeconomic analysis (TEA) of various Power-to-X conversion pathways, with an emphasis on modelling end-use scenarios (such as chemical manufacturing, green steel production, etc.). In order to inform and determine the commercial feasibility of these pathways, the student will use and build on existing TEA models and frameworks developed at GlobH2E. Hence a background in technoeconomic analysis, project design, simulation tools like Aspen/DWSIM, Excel VBA Programming, HOMER, excel and python coding would be beneficial, but not essential. 

$37,684 per annum (2024 rate, indexed) for 3.5 years. International candidates will receive a tuition fee scholarship.

Radio Interferometry is undergoing an epoch-defining expansion, with many next-generation instruments in final planning or under commissioning (e.g., SKA, ngVLA, ngEHT and their pathfinders). Nevertheless, with these great opportunities come some great challenges, and perhaps most pressingly, we must update our computational approaches to match the updated infrastructure.

Machine Learning approaches are ideal for addressing these ‘big data’ questions, with many new applications being discovered almost daily. The opportunities are practically infinite. One particularly promising approach is the use of Graphical Neural Networks (GNNs).

The traditional approach for imaging radio-interferometric data has been to convert the 3D temporally sampled data to a 2D regular grid, then Fourier transform and iteratively correct for the instrumental effects. However, this approach’s multitude of approximations limits its accuracy and scalability. GNNs provide a powerful alternative by directly operating on the irregular data domains sampled by the interferometer.

GNNs extend neural networks to process data represented as graphs, capturing node features and graph topology. For interferometers, the visibilities can be described as node features on a graph defined by the antenna locations and baseline connections. This provides a morphological match between the data domain and the machine learning framework, massively enhancing convergence compared to operating on gridded data.

We would apply GNN imaging to real data from the SKA pathfinders (MWA, ASKAP) and early science (or simulated) SKA datasets, testing the limits of current computation capabilities. We expect this to become a major focus for the SKA Data Processing pipeline, particularly for scales beyond AA2 in 2026.

The outcome of the PhD would be an innovative new approach to robust, scalable imaging in the SKA era, enabling crucial science applications for SKA, ngVLA, and ngEHT. This experience would provide valuable expertise in cutting-edge GNN development with prospects for broader academic and industry applications.

Read more about the project here.

The Australian Government’s Research Training Program (RTP) provides funding to support both domestic and international students undertaking Research Doctorate and Research Master’s degrees. At UWA, RTP funding is used to support eligible students through the following types of scholarships:

International RTP Tuition Fees Offset Scholarships - awarded to a limited number of international students, via a competitive selection process.

RTP Stipend Scholarships (living allowance) - awarded to a limited number of domestic and international students, via a competitive selection process. The current value in 2026 is $38,110 per annum.

RTP Allowances - awarded to assist students with ancillary costs of Higher Degree by Research, such as relocation expenses.

This PhD project has the potential to save the Square Kilometre Array Observatory millions in storage and processing costs!

The SKA will produce up to 1 TB/s of raw, uncompressed data streaming into the dedicated processing facilities in both South Africa and Australia. This data will then be processed using a variety of scientific workflows and the results finally stored in multiple facilities around the world. There are now very sophisticated algorithms available, which allow both lossy and lossless compression on multiple scales, adaptive and dedicated to the type of axis in multi-dimensional data cubes. This includes JPEG2000 and also MGARD.

The project aims to apply such lossy compression methods in a systematic way to radio astronomical data along the processing chain and provide a quantitative assessment of the  impact on the science results. More concretely compression can be applied during the reception stage, when the data is streaming into the processing facilities, on intermediate data products and/or on the final data products. Each of those use cases will need to be carefully constructed, executed and analyzed as part of this project. In order to establish the ground truth, we will use simulated data sets, but then also move on to hybrid and real data sets. This will require to run actual, complex data reduction workflows on these data sets and understand the mathematical concepts behind the individual steps. It will also be required to carefully select science quality metrics for the assessment of the impact.

Questions to be answered include:

Where in the workflows is it most efficient, but is still not causing critical loss of scientific information?How much scientific information is lost, depending on the compression level?Can and should we apply it in more than one place?What is the impact on data I/O and archive costs?A more advanced question would be: What is the relation, if any, between the compression and some of the core radio astronomy sky reconstruction algorithms?

Read more about the project here.

The Australian Government’s Research Training Program (RTP) provides funding to support both domestic and international students undertaking Research Doctorate and Research Master’s degrees. At UWA, RTP funding is used to support eligible students through the following types of scholarships:

International RTP Tuition Fees Offset Scholarships - awarded to a limited number of international students, via a competitive selection process.

RTP Stipend Scholarships (living allowance) - awarded to a limited number of domestic and international students, via a competitive selection process. The current value in 2026 is $38,110 per annum.

RTP Allowances - awarded to assist students with ancillary costs of Higher Degree by Research, such as relocation expenses.

Our ability to study our universe is defined by the power of our telescopes. Technologies developed for quantum communications and quantum sensors have the potential to revolutionize astronomy by increasing their sensitivity and resolution. Techniques developed from quantum optics research allow us to extract more information from each photon and even achieve super-resolution — resolution beyond what can be achieved with classical technologies. Telescopes using these technologies would enable us to image Earth-like exoplanets, probe the event horizons of black holes, and reveal the formation mechanism of stars and planetary systems.

PhD topics include:

• Quantum interferometers — Adapting technologies, such as quantum memories, and tools from quantum optics to demonstrate large-scale quantum imaging interferometers capable of surpassing the resolution of any existing telescope.
• Quantum telescopes — Developing lab-scale quantum imaging techniques and theory into practical tools for astronomy, including testing these systems on actual telescopes and observations.
• Digital intensity interferometry — Intensity interferometry infers information about astronomical objects through correlation of amplitude information. This work will develop and extend the capabilities of this technique using modern digital signal processing.
• Giving back to quantum — Taking the knowledge and advancements made in the pursuit of adapting quantum technologies to astronomy and applying them to improve quantum communications and quantum sensing.

The student will work as part of the Astrophotonics Group (www.icrar.org/astrophotonics) at the International Centre for Radio Astronomy Research (ICRAR) with a multidisciplinary team with expertise in astronomy, physics, and engineering. The student will have the opportunity to work in a world-class optical metrology laboratory, develop skills in experimental physics and engineering, and collaborate with research groups and observatories from across Australia and around the world.

Read more about the project here.

The Australian Government’s Research Training Program (RTP) provides funding to support both domestic and international students undertaking Research Doctorate and Research Master’s degrees. At UWA, RTP funding is used to support eligible students through the following types of scholarships:

International RTP Tuition Fees Offset Scholarships - awarded to a limited number of international students, via a competitive selection process.

RTP Stipend Scholarships (living allowance) - awarded to a limited number of domestic and international students, via a competitive selection process. The current value in 2026 is $38,110 per annum.

RTP Allowances - awarded to assist students with ancillary costs of Higher Degree by Research, such as relocation expenses.

With the commissioning of the Square Kilometre Array, radio observations and particularly dynamic objects (fast radio bursts, supernovae, gamma-ray bursts, etc.), due to the greater capability of the next-generation instruments, are receiving more focus. Simultaneously, the volume of data produced by such instruments makes detecting transients a data-driven endeavour. Transient events often represent some of the universe’s most extreme conditions. Therefore, they are of great scientific interest. Transients are detected early in radio astronomy processing pipelines, with real-time detection as the ultimate goal. Spiking Neural Networks (SNNs) borrow more heavily from biological inspiration than Artificial Neural Networks (ANNs); most importantly, their dynamics vary in time, making them helpful in processing spatiotemporal data, like radio telescope visibility data.

Spiking Neural Networks are a very new technology for radio astronomy, with few published results to date. This project would build on recent work tasking SNNs with detecting Radio Frequency Interference (RFI). Transient detection events occur at a similar stage in the processing pipeline and often present similarly to RFI. When paired with neuromorphic computing hardware that efficiently executes SNNs, massive energy- efficiency gains could be realised, translating into considerable operational benefits in radio astronomy. This project is, therefore, significant from an engineering and scientific perspective. This PhD would involve developing and testing SNN architectures to detect transient events in radio astronomy visibility data, applied to simulated and real data from existing instruments.

Read more about the project here.

The Australian Government’s Research Training Program (RTP) provides funding to support both domestic and international students undertaking Research Doctorate and Research Master’s degrees. At UWA, RTP funding is used to support eligible students through the following types of scholarships:

International RTP Tuition Fees Offset Scholarships - awarded to a limited number of international students, via a competitive selection process.

RTP Stipend Scholarships (living allowance) - awarded to a limited number of domestic and international students, via a competitive selection process. The current value in 2026 is $38,110 per annum.

RTP Allowances - awarded to assist students with ancillary costs of Higher Degree by Research, such as relocation expenses.

The ideal candidate will hold a Bachelor Honours degree or Masters degree in Astronomy with some experience in compu- tational methods; or a Bachelor Honours degree or Masters degree in Computer Science with an interest in Astronomy and High Performance Computing.

Skills

• Python
• Pytorch, Tensorflow or other Deep Learning experiences favoured
• High Performance computing environments (Slurm, MPI) also appreciated 

Training and Development

The candidate will be responsible for designing and evaluating SNN architectures, learning how to perform large-scale SNN simulation and deep learning experiments on HPC platforms, and potentially collaborating with SynSense, a provider of commercial neuromorphic hardware.  

Pulsars, rapidly rotating neutron stars emit periodic radio signals and represent some of the most extreme objects in the known universe. Detecting these rapidly varying signals in radio telescopes occurs very early in the overall signal-processing pipeline and is therefore a real-time extreme computational challenge. Traditional detection methods struggle to balance detection performance with computational performance, necessitating innovative approaches to handle what is essentially a detection challenge in a rapid spatio- temporal signal. Current state-of-the-art approaches leverage FPGAs and GPUs (often together) in the search for the highest levels of accuracy and energy efficiency.

Neuromorphic computing and Spiking Neural Networks (SNNs) present a compelling approach to this challenge. By emulating the time-varying behaviour of biological neurons, SNNs are uniquely suited to processing complex, dynamic data, such as audio signals or event-based video streams. SNNs are a very new technology for radio astronomy, with only few published results to date. This project will investigate the potential of SNNs for real-time, scalable pulsar detection, aiming not only to overcome the limitations of conventional methods but also to extend the boundaries of SNN applications to novel and demanding astrophysical tasks. 

This is an opportunity for a PhD in a rapidly growing area in Machine Learning. Spiking neural networks (SNNs) much more closely mimic the operation of a real brain than traditional artificial neural networks (ANNs) by reproducing the spike-driven nature of real neurons. There is also the opportunity to collaborate with SynSense AG, a startup developing neuromorphic hardware to execute SNNs at low power.

Read more about the project here.

The Australian Government’s Research Training Program (RTP) provides funding to support both domestic and international students undertaking Research Doctorate and Research Master’s degrees. At UWA, RTP funding is used to support eligible students through the following types of scholarships:

International RTP Tuition Fees Offset Scholarships - awarded to a limited number of international students, via a competitive selection process.

RTP Stipend Scholarships (living allowance) - awarded to a limited number of domestic and international students, via a competitive selection process. The current value in 2026 is $38,110 per annum.

RTP Allowances - awarded to assist students with ancillary costs of Higher Degree by Research, such as relocation expenses.

The ideal candidate will hold a Bachelor Honours degree or Masters degree in Astronomy with some experience in compu- tational methods; or a Bachelor Honours degree or Masters degree in Computer Science with an interest in Astronomy and High Performance Computing.

Skills

• Python
• Pytorch, Tensorflow or other Deep Learning experiences favoured
• High Performance computing environments (Slurm, MPI) also appreciated 

Training and Development

The candidate will be responsible for designing and evaluating SNN architectures, learning how to perform large-scale SNN simulation and deep learning experiments on HPC platforms, and potentially collaborating with SynSense, a provider of commercial neuromorphic hardware.  

The emergence of AI teaching assistants marks a new era in education, where non-human entities are integrated as tutors, aides, consultants, or even "machine instructors." 

This project aims at exploring the applications of AI in education, which may involve the design, implementation and evaluation of AI-powered teaching tools. 
Faculty of Engineering 

This project aims to understand how to build AI systems that humans can trust. It does so by studying how to make such systems fair, explainable, auditable, preserving of privacy and verifiable.

Outputs will include tools to build trustworthy AI systems, as well as policy recommendations to complement the technical tools. This should provide significant economic and societal benefits as decisions in both the public and private sector are increasingly being handed over to computers.

$37,684 per annum (2024 rate, indexed) for 3.5 years. International candidates will receive a tuition fee scholarship.

$37,684 per annum (2024 rate, indexed) for 3.5 years. International candidates will receive a tuition fee scholarship.

$37,684 per annum (2024 rate, indexed) for 3.5 years. International candidates will receive a tuition fee scholarship.

This project aims to pioneer innovations in green civil engineering by developing first-of-its-kind porous structures for Australian sustainable environment. It establishes novel graded porous geometries in cementitious structures for superior stiffness and thermal insulation. The lightweight yet robust structures with minimal cement usage are crucial to mitigating carbon footprints in civil construction and building operation with huge emissions. The project expects to develop new knowledge and advanced simulations in porous composites. This will help Australia growing green civil industries with significant economic benefits and achieving the Net Zero Plan via saving building operation energy and reducing construction emissions and waste.

The candidate will work closely with industrial partners and academics from different Universities/Schools. The success of this project will bring the candidate
1) exceptional research achievements; 
2) wide industrial and academic connections; 
3) a great career path as a composite engineer/researcher in civil and mechanical engineering.

$38,438 per annum (2025 rate). Other supports will also be provided, including opportunities to assist teaching and to attend international conferences.

$37,684 per annum (2024 rate, indexed) for 3.5 years. International candidates will receive a tuition fee scholarship.

AI-Enhanced Battery Management and Safety for Battery Energy Storage Systems. 
This project will develop advanced battery management and safety technologies for next-generation energy storage systems, with a focus on improving performance, reliability, and lifespan. Working with industry partners, it will integrate artificial intelligence, physics-based modelling, and real-time sensing to accurately assess battery health, predict failures, and optimise operation under diverse conditions.

The research addresses critical challenges in deploying large-scale and second-life batteries for renewable energy integration, electric mobility, and grid stability. By detecting faults early and enhancing control strategies, the project aims to reduce downtime, improve safety, and lower lifecycle costs.
Outcomes include validated algorithms, prototype systems, and guidelines for industry adoption. This work will accelerate Australia's transition to a cleaner, more resilient energy system, strengthen local manufacturing and recycling capabilities, and create commercial opportunities in global energy storage markets. 

$39,206 per annum (2026 rate) up to 3.5 years. $10,000 industry top-up.

For more information about this project please contact A/Prof Huadong Mo. 
https://www.unsw.edu.au/research/hdr/our-projects/ai-enhanced-battery-management-and-safety-for-battery-energy-storage-systems.

This project will develop a framework to optimise the schedule and operation of electrified transportation fleets. 

It will predict batteries performance, detect anomalies in real time, manage schedule uncertainties, adapt to battery health, charger availability and unexpected delays.

Expected outcomes include improved reliability and efficiency, extended battery life and reduced operational costs. 

Are you ready to unlock the micro mechanisms of fracture in ultra-high strength steels (UHSS) and shape the next generation of automotive steels? We are offering a fully funded PhD position to develop a new in-situ testing technology that links steel microstructure evolution directly to fracture mechanisms during metal forming. 

What you’ll do

• develop and implement a novel in-situ testing procedure that links microstructural characteristics of ultra-high strength steels (UHSS) to fracture mechanisms.
• design and optimise dedicated specimen geometries to impose well-defined strain path conditions representative of industrial forming operations.
• conduct combined in-situ microstructure characterisation and deformation tracking to quantify how phase distribution, morphology and evolution influence fracture initiation and propagation.
• establish direct correlations between strain path, microstructure evolution and fracture behaviour to support advanced micro-structure design and forming process optimisation.

Target deliverables

• a robust experimental framework for in-situ tensile testing in an scanning electron microscopy (SEM) that enables systematic analysis of microstructure evolution and fracture mechanisms.
• fundamental understanding of microstructure effects on fracture that can be directly implemented in industrial Research and Development (R&D) environments for future UHSS microstructure design and optimisation.

Why this project is unique

• industry-embedded research with global impact through collaboration with Baosteel, one of the world’s leading steel producers.
• direct pathway to industrial implementation, with outcomes designed for immediate integration into advanced UHSS development programs.
• rare integration of mechanics and microstructure science, combining controlled strain-path material testing with in-situ microstructural analysis.
• strategic relevance to electric vehicle lightweighting, supporting the safe and widespread application of next-generation UHSS in future EV structures.
• strong career development opportunities, positioning the candidate at the interface of experimental mechanics, materials modelling, and industrial metal alloy innovation.

This scholarship is available over three years and offers:

• a stipend of $35,000 per annum tax exempt

For international students, the awardee will also receive:

• tuition fees offset for the duration of four years
• single Overseas Student Health Cover policy for the duration of the student visa.

We are seeking highly motivated applicants with a background in mechanical engineering, materials (metal) engineering, manufacturing engineering, or closely related disciplines, who have a strong interest in:

• experimental mechanics and deformation testing
• microstructure characterisation and material behaviour
• finite Element Analysis and sub-routines
• translating fundamental materials science into industrial application

Graduates who are enthusiastic about working at the interface of academia and industry, and who are keen to see their research implemented in real-world steel development programs, are strongly encouraged to apply.

This project aims to develop the most advantageous combinations of electrolyte and binder through engineering the electrode structures for compatibility with advanced liquid or solid-state electrolytes. Targeted polymer binders will include those based on the non-fluorinated poly(dimethyldiallylammonium) ionomer and naturally occurring polymers such as carrageenan, alginate and carboxymethyl cellulose. These can then be imbibed with electrolytes containing ionic liquids or organic ionic plastic crystals with the goal of imparting ionic conductivity functionality for higher rate charge/discharge performance or developing the electrodes into a solid-state structure for pairing with a solid electrolyte.

Sodium-ion batteries are becoming an increasingly popularised lower-cost alternative to lithium-ion batteries, however electrolytes for sodium-ion batteries are less developed than the lithium-based counterparts. Ionic liquid electrolytes developed at Deakin are a new electrolyte class that offers superior safety than conventional flammable and volatile electrolytes. Solid-state ceramic electrolytes developed at Bayreuth have enormous potential in overcoming some of the limitations faced with lithium-based ceramics.

Electrode composite structures will also be investigated, focusing mostly on using well-studied active materials such as hard carbon anodes and sodium vanadium phosphate (or fluorophosphate) cathodes available in Bayreuth.

You will be awarded with a doctoral degree from each university. The program runs for three years, and you will spend at least 12 months at the University of Bayreuth and the remainder at Deakin University.

This scholarship is available over three years and offers:

• a stipend of $35,550 per annum tax exempt (2025 rate)
• at least 12 months of the total period of the program at University of Bayreuth.

For international students, the awardee will also receive:

• single Overseas Student Health Cover policy for the duration of the student visa
• full tuition fee waiver for up to four years
• travel allowance (approximately $3,000) to support travel between universities.

To be eligible you must:

• meet the PhD entry requirements of both Deakin University and University of Bayreuth, including H1 or H1 equivalence and English language proficiency criteria
• enrol full time
• be able to physically locate to both University of Bayreuth (Germany) and Deakin University (Australia).

Are you ready to push the boundaries of design, technology, and human performance?

Join a cutting-edge PhD research project at the forefront of innovation; where sports science, assistive technology, and advanced manufacturing collide!

This PhD project explores the design of personalised, lightweight, and multi-functional structures for the sports and assistive technology sectors. It integrates computational design, advanced additive manufacturing, and intelligent systems to develop user-specific solutions that enhance performance, comfort, and accessibility.

The research will focus on polymeric lattice structures with tunable mechanical properties - such as flexibility, energy absorption, and directional stiffness - fabricated using cutting-edge 3D printing and sensing technologies. Experimental and simulative methods will be used to analyse material behaviour across scales, supported by nonlinear computational modelling and AI-driven optimisation.

Guided by systems thinking, the project will develop adaptive, sustainable, and user-centred design workflows. Outcomes will contribute to the fields of structural modelling, smart materials, and inclusive design, with applications in rehabilitation, elite sport, and mobility.

Candidate profile

We seek a candidate with strong expertise in computational design, additive manufacturing, and nonlinear structural modelling. A background in mechanical, biomedical, or materials engineering is essential, along with experience in experimental methods, finite element analysis, and AI-assisted design.

You will be awarded with a doctoral degree from each university. The program runs for three years, and you will spend at least 12 months at the University of Bayreuth and the remainder at Deakin University.

This scholarship is available over three years and offers:

• a stipend of $37,450 per annum tax exempt (2026 rate)
• at least 12 months of the total period of the program at University of Bayreuth.

For international students, the awardee will also receive:

• single Overseas Student Health Cover policy for the duration of the student visa
• full tuition fee waiver for up to four years
• travel allowance (approximately $3,000) to support travel between universities.

To be eligible you must:

• meet the PhD entry requirements of both Deakin University and University of Bayreuth, including H1 or H1 equivalence and English language proficiency criteria
• enrol full time
• be able to physically locate to both University of Bayreuth (Germany) and Deakin University (Australia).

This project aims to develop AI-based monitoring and estimation models for battery maintenance in Australian heavy industries. Xcel Tech provides next-generation technological solutions to electric trucks for the mining industry, the research team will develop novel and application-based models for specific batteries used in Australian heavy industries, such as mining and agriculture, for the purpose of battery health monitoring, optimal charging and fault diagnosis.

Due to the uniqueness of Australia’s mining sites, such as high temperature, low humidity and poor internet connection, a new plug-and-play software model and/or hardware device is needed to provide real-time monitoring and fault diagnosis for batteries used in these harsh conditions. These hardware devices and software models can help provide a range of features and functions, including but not limited to:

• predictive maintenance, i.e. to predict when maintenance is due
• condition monitoring, i.e. detecting abnormalities such as temperature fluctuations, voltage variations or electrolyte levels
• optimal charging strategies, i.e. dynamically adjusting charging schedules based on demand and battery health
• energy management integration, i.e. working with control algorithms to collaboratively manage battery usage.

You will be supervised by Dr Samson Yu at School of Engineering and Associate Professor Wei Luo at School of Information Technology. This multidisciplinary team will provide expertise necessary for the candidate to succeed in theoretical and applied research in this project.

Industry partner Xcel Tech will provide batteries used in heavy industries for testing and possible implementation of the developed software models, improving battery efficiency and prolonging battery life and contributing to the decarbonization of Australian industry. 

This PhD project is in collaboration with Xcel Tech. The project supports the research towards clean energy and battery storage technology.

This scholarship is available over three years (possible six-month extension) and offers:

• a stipend of $45,550 per annum tax exempt (2025 rate)
• a relocation allowance of $500–1,500 (for single to family) for students moving from interstate
• contribution to research purposes including travel: $1,500 per annum for three years.

For international students, the awardee will also receive:

• tuition fees offset for the duration of four years
• single Overseas Student Health Cover policy for the duration of the student visa.

Additional desirable criteria:

• knowledge of electrical engineering or information technology, with background knowledge in circuits and systems, artificial intelligence, battery operations and/or broad knowledge in electronics or machine learning
• industry work experience in battery industry or energy industry, with a deep understanding of industry practices
• possess strong oral and written communication skills as they will be required to meet with their academic and industry stakeholders on a regular basis
• ability to travel between Deakin and the industry partner at least once a year for research finding communication and presentation.

This PhD project aims to advance the performance and reliability of geothermal heat pump systems for sustainable buildings by integrating cutting-edge artificial intelligence techniques.

The research will analyse real-world system performance against design expectations, identify and resolve operational inefficiencies in collaboration with industry partners, and develop AI-driven optimisation strategies to enhance temperature control, flow rates, and coefficient of performance (COP).

Through this work, the project seeks to unlock greater energy efficiency and emissions reduction in the built environment, contributing to global efforts to decarbonise a sector responsible for over a third of energy use and CO₂ emissions.

The successful candidate will work closely with leading organisations, including PICAC, IAPMO, and the Lawrence Berkeley National Laboratory (USA).

If you're ready to lead research on geothermal energy for buildings we encourage you to apply.

The scholarships is available over three years (possible six-month extension) and offers:

• a stipend of $45,550 per annum tax exempt (2025 rate)
• a relocation allowance of $500–1,500 (for single to family) for students moving from interstate
• contribution to research purposes including travel of $1,500 per annum for three years.
• a once-off $5,000 conference travel allowance
• an annual research allowance of $1,100 (per year)

For international students, the awardee will also receive:

• tuition fees offset for the duration of four years
• single Overseas Student Health Cover policy for the duration of the student visa.

Professor Andreas Wicenec | [email protected]; Director, Data Intensive Astronomy

Dr. Fuling Chen | [email protected]; Research Fellow, Data Intensive Astronomy

Machine learning models, including linear regression, ensemble methods like random forests, and deep neural networks, have transformed medical research by enabling breakthroughs in diagnostics, drug discovery, and personalized treatment. However, these models often function as "black boxes," offering little insight into how they arrive at predictions. This lack of interpretability hinders trust and adoption in healthcare, where understanding the reasoning behind decisions is critical for clinical validation and patient safety.

This PhD project aims to address the urgent need for explainable AI (XAI) in medical research by developing algorithms that combine predictive accuracy with clear, interpretable outputs. Emerging approaches like Kolmogorov-Arnold Networks (KANs) and techniques such as SHAP or LIME provide pathways to make AI decisions transparent. By creating models that explain their processes and results, this research will empower medical professionals to validate AI outputs, uncover biological insights, and ensure ethical, equitable healthcare solutions.

As a PhD candidate, you will design and implement novel XAI models tailored for medical datasets, including epidemiology, genomics, and epigenetics data. Using Python and frameworks like PyTorch or scikit-learn, you will prototype algorithms, test them on real-world medical benchmarks, and evaluate both accuracy and interpretability. You will collaborate with AI experts and clinicians, contributing to publications in top journals and conferences.

Your work will advance the field of medical AI by creating trustworthy, interpretable models that could improve disease detection or treatment planning. We welcome candidates with a background in computer science or related fields, proficiency in programming, and a passion for impactful research.

Read more about the project here.

This project proposes novel low-cost miniature devices for spectral, spatial and temporal manipulation of terahertz waves realised using a unified platform based on a single material and fabrication technology sufficiently generic to span the entire very broad terahertz band. It inherently overcomes the most hindering issue of current terahertz instruments relating to the limited span of the spectrum each tool can cover and the high costs associated with increasing this span; removing the need for making spectral band compromises in the design of future tools. The intended outcome is a platform for terahertz spectroscopic imaging, target recognition, detection of chemical composition of objects, and future high-bandwidth communications.

We have multiple PhD scholarships available, providing an excellent environment for growth and professional development. As a part of our team, you will have access to cutting-edge resources and expertise, incl. the Western Australian Node of the Australian National Fabrication Facility; enabling you to make significant contributions in science and engineering. 

Read more about the project here.

This project proposes novel low-cost miniature devices for spectral, spatial and temporal manipulation of terahertz waves realised using a unified platform based on a single material and fabrication technology sufficiently generic to span the entire very broad terahertz band. It inherently overcomes the most hindering issue of current terahertz instruments relating to the limited span of the spectrum each tool can cover and the high costs associated with increasing this span; removing the need for making spectral band compromises in the design of future tools. The intended outcome is a platform for terahertz spectroscopic imaging, target recognition, detection of chemical composition of objects, and future high-bandwidth communications.

We have multiple PhD scholarships available, providing an excellent environment for growth and professional development. As a part of our team, you will have access to cutting-edge resources and expertise, incl. the Western Australian Node of the Australian National Fabrication Facility; enabling you to make significant contributions in science and engineering. The Australian Government’s Research Training Program (RTP) provides funding to support both domestic and international students undertaking Research Doctorate and Research Master’s degrees. At UWA, RTP funding is used to support eligible students through the following types of scholarships:

International RTP Tuition Fees Offset Scholarships - awarded to a limited number of international students, via a competitive selection process.

RTP Stipend Scholarships (living allowance) - awarded to a limited number of domestic and international students, via a competitive selection process. The current value in 2026 is $38,110 per annum.

RTP Allowances - awarded to assist students with ancillary costs of Higher Degree by Research, such as relocation expenses.

The relative inefficiency of existing top-performing infrared detectors at room temperature is a major roadblock to miniaturisation and precludes their use in drones and space applications where weight is critical. New approaches to infrared detection using the integration of subwavelength elements into mercury cadmium telluride detectors will enable the miniaturisation and lowering of cost of portable electronic devices for applications such as astronomy, security & surveillance, agriculture, night vision, remote sensing and medical imaging.

We aim to increase the resolution/sensitivity of infrared imaging devices, along with reducing the size, weight and power (SWaP) by combining imaging arrays with meta-materials, micro-lenses, and engineering the material properties. We are exploring novel materials and smart engineering of the detectors to create novel devices.

We have also developed tiny infrared resonators for remote thermal sensing and imaging utilising metamaterials. These are fixed or electrically tunable structures which will only pass a specific wavelength of light just before entering the photodetector or imaging array. The aim is to achieve mercury-cadmium-telluride imaging arrays with lower cross-talk, improved modulation transfer function (MTF), and higher operating temperature (HOT).

We have multiple PhD scholarships available, providing an excellent environment for growth and professional development. As a part of our team, you will have access to cutting-edge resources and expertise, incl. the Western Australian Node of the Australian National Fabrication Facility; enabling you to make significant contributions in science and engineering. 

Read more about the project here.

Applicants are encouraged to apply for a RTP scholarship in the appropriate scholarship round which are open thus:
International applicants - 1 July to 30 Aug
https://www.uwa.edu.au/study/research/research-scholarships 

Once suitable candidates are identified the opportunity may end before the closing date.

Manipulating light has been the essence of optics, from shaping glasses to make lenses and telescopes to using pinhole cameras to capture images. Traditional optical components have curves and edges making them thick, limiting miniaturisation. With meta-optics, one can go beyond traditional optics by employing nanotechnology to create ultra-thin and flat structures to achieve the same functions and even extend performance. To manipulate light with meta-optics, we focus on optical metasurfaces equipped with MEMS-enabled dynamic reconfigurability.

Metasurfaces enable much stronger tunability and reconfigurability than any natural non-structured material. This makes meta-optics a promising candidate for future flat devices that will dynamically control the wavelength, amplitude, phase, and polarisation of light. To create futuristic optical devices for holography and remote imaging, these capabilities are essential.

This research program aims to create tunable metadevices where the properties of light can be controlled and programmed dynamically in real time for image processing applications. We have multiple PhD scholarships available, providing an excellent environment for growth and professional development. As a part of our team, you will have access to cutting-edge resources and expertise, incl. the Western Australian Node of the Australian National Fabrication Facility; enabling you to make significant contributions in science and engineering. 

Read more about the project here.

Applicants are encouraged to apply for a RTP scholarship in the appropriate scholarship round which are open thus:
International applicants - 1 July to 30 Aug
https://www.uwa.edu.au/study/research/research-scholarships 

Once suitable candidates are identified the opportunity may end before the closing date.

Ground rotation sensors have wide applications, such as precision instrumentation, environment monitoring, and rotational seismology, as well as for improving the sensitivities of gravitation wave detectors.  Currently available rotation sensors have issues of either low sensitivities or too fragile/too large to be used in the field. At UWA we are developing a compact, and robust with a high sensitivity rotation sensor using many innovative technologies.  This PhD project is to build, characterise and field test the rotation sensor. 

The student will have the opportunity to work with a team of physicists and engineers in the UWA gravitational wave instrumentation group and develop skills in precision mechanics and control, optical readout system and noise analysis. This work will be conducted in collaboration with research groups from across Australia and around the world.

Read more about the project here.

Applicants are encouraged to apply for a RTP scholarship in the appropriate scholarship round which are open thus:
International applicants - 1 July to 15 Sep
https://www.uwa.edu.au/study/research/research-scholarships 

Once suitable candidates are identified the opportunity may end before the closing date.

Project

Are you curious about how large language models “think” and how they reflect human personalities? In this project, you’ll explore how AI text reveals psychological traits, and build systems that infer and steer personality in AI models. You’ll work with real prompt data, apply NLP and machine-learning techniques, and contribute to new approaches in human-AI alignment.

Requirements

Interest in multidisciplinary work. Very good programming skills. Above all I am looking for students who have a positive attitude and are willing to learn and explore. 

About me

I am a Senior Lecturer in Computer Science. I also lead the Network Analysis and Social Influence Modelling (NASIM) Lab at the School of Physics, Maths and Computing, where we work at the intersection of computer science and social psychology. The lab currently includes 3 PhD students, a research associate, and several honours and MPE students, creating a vibrant, collaborative, and supportive environment. Our lab has access to state-of-the-art GPUs and cloud platforms, so computational power is never a problem. Students work closely together, share ideas, and have fun tackling ambitious research problems that make a real-world impact. 

Read more about the project here.

The Australian Government’s Research Training Program (RTP) provides funding to support both domestic and international students undertaking Research Doctorate and Research Master’s degrees. At UWA, RTP funding is used to support eligible students through the following types of scholarships:

International RTP Tuition Fees Offset Scholarships - awarded to a limited number of international students, via a competitive selection process.

RTP Stipend Scholarships (living allowance) - awarded to a limited number of domestic and international students, via a competitive selection process. The current value in 2026 is $38,110 per annum.

RTP Allowances - awarded to assist students with ancillary costs of Higher Degree by Research, such as relocation expenses.

Radio astronomy is producing huge multi-dimensional data cubes, which require the application of complex computational workflows on High Performance Compute (HPC) clusters. These workflows require optimization of I/O. Even when assuming that we would be able to load all the data into the cluster memory, there will be enormous amounts of inter and cross-node communication required to get the data from one process to the next. HPC clusters are inherently non homogeneous in terms of I/O performance within a single computer (due to NUMA architectures) and worse across multiple computers due to the network topology of the cluster and even worse when it comes to accessing data on the (shared), multi-level file system. Access patterns in typical radio astronomy algorithms on the other side are highly dependent on the algorithms applied to the data and thus ultimately on the science goals. These access patterns can differ from the one extreme of being perfectly aligned with the native order of the data cube to the other extreme of being orthogonal to it. Having such an issue on a single machine has severe impacts on overall performance already, but on a cluster it might lead to a situation where every worker of a N times distributed algorithm initiates access to pieces of data residing on many, if not all, nodes of the cluster. In this project we will investigate the effect of such conflicting access patterns and try to address the issue by distributing the multi-dimensional data using so called space filling curves such like Hilbert curves. Thus it is necessary to identify at least the minimal set of parameters required to adjust the data distribution to differing target HPC systems.

Read more about the project here.

The Australian Government’s Research Training Program (RTP) provides funding to support both domestic and international students undertaking Research Doctorate and Research Master’s degrees. At UWA, RTP funding is used to support eligible students through the following types of scholarships:

International RTP Tuition Fees Offset Scholarships - awarded to a limited number of international students, via a competitive selection process.

RTP Stipend Scholarships (living allowance) - awarded to a limited number of domestic and international students, via a competitive selection process. The current value in 2026 is $38,110 per annum.

RTP Allowances - awarded to assist students with ancillary costs of Higher Degree by Research, such as relocation expenses.

The selection of applicants for the award of higher degree research scholarships at Adelaide University involves consideration of your academic credentials and demonstrated research experience.

For detailed information regarding eligibility criteria, including specific GPA requirements and program structure please refer to the relevant Adelaide Graduate Research School (AGRS) Academic Program Rules for higher degree by research qualifications.

International applicants must provide evidence of meeting the minimum English language proficiency requirements for their application to be considered. Refer to the AGRS website for requirements.