We study the statistics of turbulent, magnetised gases, relevant to the structure and evolution of the interstellar medium, and the formation and evolution of stars and galaxies. We use a combination of supercomputer simulations, theory, analytical calculations, and comparison to observations.

Some experience and interest in programming (e.g., with python) is welcome, but not a strict requirement.

This research project can be extended, and supported with additional funding, beyond the standard duration (12 weeks) of the FRT program. This possibility and duration of extension will be considered on a case-by-case basis and discussed with the shortlisted candidate during the selection process. 

A key goal of the WALLABY HI survey on the Australian SKA Pathfinder is to map the density and velocity field of the local universe. Galaxies' distances and peculiar velocities will be measured using the Tully-Fisher relation between linewidth and absolute magnitude. The first step in this program is to determine the selection function for galaxies with well-measured HI velocity line widths. The second step is to use a new method for jointly fitting the Tully-Fisher relation and the parameters describing the velocity field. This project will address the first of these steps, with the goal of accurately determining the selection function for WALLABY HI linewidth measurements.

Basic knowledge of Python is highly desirable.

This research project can be extended, and supported with additional funding, beyond the standard duration (12 weeks) of the FRT program. This possibility and duration of extension will be considered on a case-by-case basis and discussed with the shortlisted candidate during the selection process. 

Spatial heterodyne spectrographs (SHS) offer compact, high-resolution spectrometry with numerous advantages, such as no moving parts, and cost-effectiveness.  This makes it ideal for future space-based spectroscopic instruments for astronomical and remote sensing observations from small-satellite platforms such as CubeSats.  This project encompasses science simulation, instrument modelling, electro-optical, and system design of spectroscopic instruments with a focus on UV astronomy. 

Background in scientific programming (e.g: python) and data analysis is required.

The nature of dark matter and the formation of the first galaxies are both unsolved mysteries. My recently ARC-funded project aims to build an innovative framework to leverage future 21-cm experiments to observe cosmic dawn and to forecast the optimal constraints on dark matter physics.

Note: Projects are available that can be either astrophysics or machine learning-focused.

Background in statistics and/or machine learning; proficient in Python and/or C.

For the suitable candidate, the duration of this project can be extended to a total period of up to 24 weeks, supported by additional funding for extended living costs beyond the standard duration of the FRT program.

There are giant, gamma-ray emitting lobes emerging from the nucleus of the Milky Way. These structures, known as the Fermi Bubbles, may be signatures of an outburst from the Galaxy’s supermassive black hole within the last million years. Alternatively, they may be unconnected to the black hole and due, instead, to star formation and related supernovae occurring in the centre of the Milky Way over much longer time periods. An important question bearing on the mystery of the origin of the Fermi Bubbles is: what creates the Bubbles’ gamma-ray emission?

In this project, you will investigate that question using the new cosmic ray propagation code CRIPTIC developed by our group. Specifically, you will determine whether cosmic ray electrons can create the Fermi Bubble gamma-rays by up-scattering ambient light in a process called inverse Compton scattering.

Background in programming experience is required; C++ and Python would be most helpful, but other languages are also acceptable.

The Pyxis interferometer is a prototype of a high angular resolution space-based interferometer, with hardware now complete. In this project, you will help to automate the fringe acquisition in order to make internationally unique measurements of dust shells around dying solar-type stars. It will involve some work in the evenings in order to set up the interferometer and collect data.

Note: PhD candidates will only be considered if they have the requisite skills.

Background in coding skills is required, preferably a little experience in both C and Python.

For the suitable candidate, the duration of this project can be extended to a total period of up to 20 weeks, supported by additional funding for extended living costs beyond the standard duration of the FRT program.

Understanding how maternal stress interacts with offspring temperature to affect physiological performance, behaviour and life history in lizards.

Background using R for data analysis, experimentation and wet lab skills is required.

In our lab, we use genetic and genomic approaches to study the evolution of diverse taxa across space and time. In this project, you will learn and apply the latest genomic methods to reconstruct the demographic history of iconic Australian reptile and mammal species, to investigate how population size has changed over thousands of years. 

This project would suit a candidate with an interest in bioinformatics. Familiarity with command line Linux and bash is required, and the ability to run/edit basic scripts in Python/R/or or other coding languages will be beneficial. 

This project will begin to investigate how landscape features influence gene flow in a widespread, generalist lizard (Heteronotia binoei) with the aim of better understanding factors that drive early stages of population divergence — the initiation of speciation.

Some background in genetics, working with genetic data, and coding is preferable. 

Little is known about the molecular and biochemical basis that enables iconic Australian plants such as kangaroo grass to thrive in extreme environments. This project seeks to identify novel genes and biochemical pathways within these Australian plants that could enable the engineering of future climate-proof crops.

Skills in molecular biology are essential. Skills in chemistry/biochemistry would be beneficial, but not essential. Other projects listed on a webpage can also be considered by the candidates.

Scholars can also consider other projects listed on the webpage.

We are looking at the combined effects of inbreeding and temperature on fitness-related traits in the mosquitofish, to better understand how climate change will impact small populations.

Note: PhD candidates will only be considered if they have the requisite skills.

Our research involves applying molecular dynamics simulations to understand how membrane proteins function and how they can be targeted for drug development. Topics of interest include understanding the basis of mechanosensation,  exploring the membrane transporters of the malaria parasite,  immuno-active toll-like receptors as well as bio-inspired water filtration and the applications of the thermally driven diffusion.

Experience in molecular modelling or coding experience is desirable.

Note: PhD candidates will only be considered if they have the requisite skills.

Construction of synthetic heavy metal binding protein nanocages for testing in bacterial and plant expression systems.

Experience/interest in SynBio protein engineering and Golden Gate cloning preferred.

A project is available to use genetic modification approaches to identify pathogenicity genes in the wheat pathogenic fungus Zymoseptoria tritici. The project will involve subjecting the pathogen to random mutagenesis and developing a high-throughout phenotyping method for assaying the pathogenicity of the mutants on wheat.

Background knowledge in microbiology skills (culturing, aseptic technique) would be an advantage. A knowledge of simple molecular biology skills would be useful but not essential.

Australian honey bees are under attack from a recently introduced parasite, Varroa mites, which is predicted to kill almost all of them. A range of computational projects are available focused on examining evolutionary and ecological relationships between bees, mites and the viruses they vector.

Background in strong computational skills is required.

Note: PhD candidates will only be considered if they have the requisite skills.

This research project can be extended, and supported with additional funding, beyond the standard duration (12 weeks) of the FRT program. This possibility and duration of extension will be considered on a case-by-case basis and discussed with the shortlisted candidate during the selection process. 

Nano-to-atomic materials for hydrogen fuel production from the wastewater.

For the suitable candidate, the duration of this project can be extended to a total period of up to 27 weeks, supported by additional funding for extended living costs beyond the standard duration of the FRT program.     

Electrochemical synthesis of ammonia from the nitrogen-contained recourses/wastes.

For the suitable candidate, the duration of this project can be extended to a total period of up to 27 weeks, supported by additional funding for extended living costs beyond the standard duration of the FRT program.

CO2 reduction to value-added chemicals/fuels based on novel functional catalysts.

For the suitable candidate, the duration of this project can be extended to a total period of up to 27 weeks, supported by additional funding for extended living costs beyond the standard duration of the FRT program.

High-rate proton batteries for renewable energy storage and conversion.

For the suitable candidate, the duration of this project can be extended to a total period of up to 27 weeks, supported by additional funding for extended living costs beyond the standard duration of the FRT program.

Developing and applying new untargeted methods in metabolomics to rapidly and comprehensively characterise conjugated biomarkers by mass spectrometry. The project will develop new instrumental and data analysis methods to identify and characterise these biomarkers and apply these in areas such as drug development for diabetes treatment or the detection of drugs in sports.

Background in chemistry and mass spectrometry is required. Experience in metabolomics, coding and chemical synthesis is beneficial but not essential.

Prof Malcolm McLeod

Students with an interest in instrumentation development can pursue coupling EPR platform in situ electrochemistry, in situ gas exchange and in situ light (Solar, UV, LED, laser) excitation, allowing operando characterization of defects and their evolution.

Note: PhD candidates will only be considered if they have the requisite skills.

This research project can be extended, and supported with additional funding, beyond the standard duration (12 weeks) of the FRT program. This possibility and duration of extension will be considered on a case-by-case basis and discussed with the shortlisted candidate during the selection process. 

Assoc Prof Nick Cox

This project aims to magnetically label proteins for new electron paramagnetic resonance (EPR) experiments to study a protein’s structure and dynamics at low concentrations and in-cell.

Note: PhD candidates will only be considered if they have the requisite skills.

This research project can be extended, and supported with additional funding, beyond the standard duration (12 weeks) of the FRT program. This possibility and duration of extension will be considered on a case-by-case basis and discussed with the shortlisted candidate during the selection process. 

This project will magnetically label proteins for new electron paramagnetic resonance (EPR) experiments to study a protein’s structure and dynamics at low concentrations and in-cell, and then compute informative models from the measured EPR distances.

Note: PhD candidates will only be considered if they have the requisite skills.

This research project can be extended, and supported with additional funding, beyond the standard duration (12 weeks) of the FRT program. This possibility and duration of extension will be considered on a case-by-case basis and discussed with the shortlisted candidate during the selection process. 

EPR and related double resonance techniques allow us to elucidate changes in the localization of electron density (metal or ligand centred) following reduction or oxidation, and thus predict likely routes of chemical reactions/catalysis.

Note: PhD candidates will only be considered if they have the requisite skills.

This research project can be extended, and supported with additional funding, beyond the standard duration (12 weeks) of the FRT program. This possibility and duration of extension will be considered on a case-by-case basis and discussed with the shortlisted candidate during the selection process. 

Constrained peptides fill an important area of chemical space between small molecule therapies and larger antibodies. Constraining a peptide by macrocyclization or stapling can enhance metabolic stability, promote biological uptake across cell membranes, and increase binding affinity.

The Nitsche group at the ANU Research School of Chemistry has a strong interest in developing new biocompatible methods to constrain peptides and generate next-generation therapeutics.

For the suitable candidate, the duration of this project can be extended to a total period of up to 18 weeks, supported by additional funding for extended living costs beyond the standard duration of the FRT program.

Assoc. Prof Christoph Nitsche

Large language models (LLMs) have good performance in generic problems such as image captioning and question answering. However, their effectiveness in fine-grained problems such as flower categorization or facial recognition is limited. This research aims to extend LLMs' capacity in these critical areas. 

Background in computer vision and natural language processing is required.

Dr Liang Zheng

Dr Ahad Noori Zehmakan

The idea of language based security is to utilise the programming language to enforce certain security guarantees on any programs created using it. For example, Wyvern (http://wyvernlang.github.io/) enforces that only modules given to a particular module are accessible from within it - preventing unrestricted access to files, networks, or other resources. This project requires an implementation of a microservice (or several) where the task they perform is not important but how it is possible to utilise unauthorised network or other resource access is the focus of attention. Exploring then how Go (potentially with additional restrictions) can control the microservices potential access to various resources is the main point of this project and its write up.

Background in microservices or Go or programming language or compiler implementation is required.

Assoc Prof Alex Potanin

The point is to explore and compare owners-as-dominators, shallow ownership, external uniqueness, owners-as-modifiers, and other variations of ownership (and immutability) from around 20 years ago and how to support them in the modern Rust programming language. Exploring GhostCell and other Cell mechanisms and how they can help or hinder language usability is an important part of this project.

Background in compiler implementation and/or Rust is required.

Background in C/C++ for numerical code and Python for ML/Bayesian inference is preferred.

Dr Rhys Hawkins and Dr Mark Hoggard (RSES)

The Giant Magellan Telescope (GMT) requires real-time phasing of its primary mirror segments. Each instrument of GMT is required to provide phasing telemetry from guide-star images. The required phasing data is embedded in these images in a highly non-linear way. Neural-network-based solutions ought to be capable of extracting this data efficiently, and in a way that is tuned online to perform optimally under time-varying conditions.

Familiarity with AI Gym and Open AI implementations of familiar Deep RL algorithms is a plus, but also a skill that can be acquired on the job. 

The promise of software model checking and AI reasoning in the design of experiments in plasma science is clear. The successful candidate will perform an analysis of case studies in tokomak design, to answer concrete questions regarding the value proposition of AI and model checking in this setting. Existing workflows in this domain are currently undertaken using detailed simulation studies that appeal to data from real-world shots. That incumbent workflow identifies potential issues with a software model by trial and error, with issues discovered being addressed by scientists and engineers. Software codes are developed over years, an become quite complex and thereby potentially error prone, with errors often only being discovered when expensive physical experiments are undertaken. Model checking and AI are motivated here, to push the envelope on the class of common errors that can be eliminated prior to expensive computational or physical resources being expended. 

Background requirements are as follow:

Knowledge of, and otherwise the ability to acquire knowledge and understanding of tokamak physics.  For example, the following is a good reference in case you are new to this specific field:

Designing a tokamak fusion reactor—How does plasma physics fit in?, Mangiarotti, Franco Julio; Minervini, Joseph V; Freidberg, Jeffrey P. https://dspace.mit.edu/handle/1721.1/111207.

If you are familiar with the Python programming language, all you require to model the above in software is 'numpy', and if you like visualisations, then optionally 'paramak'.  Of course, if you prefer C, Rust, etc., those are also perfectly good and reasonable tools for modeling this physics with software. 

We will teach you about AI and model checking tools that can be used to determine properties of software. If you already have some knowledge about these, for example, if you have used a tool like CBMC already, that will be a plus. 

Generative artificial intelligence (AI) is a type of artificial intelligence that can generate text, images, videos, or other modality of data, using generative models. The basic procedures for Generative AI include learning a data distribution based on the training data and generating samples following the same distribution as the training data. 

Given the powerful generation ability, Generative AI tools, e.g. ChatGPT, and Stable Diffusion, have been used in various fields, such us generating source code using large language models, creating video clips or creative images based text information, performing medical diagnose based on the medical imaging and etc. 

However, we want to raise the safety issue towards Generative AI techniques before we can fully embrace them in the real world. This project aims to expose the safety issue of Generative AI and investigate solutions for safe deployment of Generative AI techniques.

Knowledge about generative AI and model robustness analysis is required.

This project is about developing fast and efficient algorithms for dynamic indoor scene reconstruction which has broad applications in AR, VR and graphics. In particular, we will investigate the implicit representations for the 3D word which can potentially lead to the compositional understanding of the 3D scene structure.

Requirement: Background knowledge in deep learning, computer vision, machine learning, computer graphics, and strong in mathematics. Programming skills in Python.

The goal of the project is to design efficient and effective strategies for aircraft allocation and prescribed burns to minimize the spread of bushfires. Ideally, the applicant should have a strong background in graph theory, probability theory, combinatorial optimization, machine learning, and programming.

Modal logic extends propositional logic wiht a unary operator, often read 'typically', 'possibly'. Resolution calculi are simple, yet efficient ways to implement decision procedures for these logics. The goal of this project is to develop resolution  calculi for all non-iterative modal logics by converting axioms to resolution rules, and adapting a completeness proof based on free-cut elimination.

Background in propositional logic is required.

The Robotics Group at the ANU School of Computing specialises in decision-making for robotics. We have multiple projects in robot planning and learning.

We have developed scalable planning methods that enable robots to work with and leverage, rather than avoid uncertainty. It resulted in a substantial increase in robustness for a wide variety of robotics problems. We are currently exploring techniques that can expand this capability further, combining planning and learning in a seamless manner, to reduce the need for model in planning and substantially reduce data requirements in learning. 

Robots deploy techniques called task and motion planning to solve complex problems where they need to solve tasks by chaining together sequences of actions and moving along the way intelligently. We are developing state-of-the-art fundamental advances in algorithms that enable robots to efficiently and robustly scale to a variety of challenging long-horizon tasks and motion planning scenarios.  

Strong programming skills, including experience with Data Structures and Algorithms are recommended. 

Background in AI and experience with robotics are a plus. A foundation of discrete mathematics and probabilities is a plus. 

The project might involve development on Linux and C++ so experience in these technologies is preferred but not necessary.

Deep reinforcement learning (DRL) techniques have demonstrated promising performance in solving complex problems, particularly in fields like robotics, autonomous systems and game playing. However, a lack of safety guarantees can be a significant concern when deploying DRL systems in real-world environments where unintended actions can have severe consequences.

To address these safety concerns and enhance the reliability and trustworthiness of DRL-based systems, we have adopted a neuro-symbolic approach by combining the strengths of deep learning with symbolic reasoning, which can provide provable safety guarantees and ensure the predictability and control of DRL models in critical applications. In this project, you are expected to improve the bi-directional mapping relationship between neural networks and symbolic reasoning engines in the existing framework to enhance the model's capability to learn and act intelligently while adhering to predefined safety constraints.

This research project can be extended, and supported with additional funding, beyond the standard duration (12 weeks) of the FRT program. This possibility and duration of extension will be considered on a case-by-case basis and discussed with the shortlisted candidate during the selection process. 

While Deep reinforcement learning (DRL) systems work well in well-defined environments where the training data covers similar samples as in the tests, it often struggles to adapt to novel or unseen situations, introducing safety and reliability concerns.

In this project, you will deal with the challenge of rapidly handling novelty and uncertainty in DRL systems. We have developed a novel method that quickly selects appropriate actions when there is a sudden change to the environment based on a reliable DRL agent. You are expected to either contribute to the existing method theoretically or practically by deploying it to different real-life domains.

This research project can be extended, and supported with additional funding, beyond the standard duration (12 weeks) of the FRT program. This possibility and duration of extension will be considered on a case-by-case basis and discussed with the shortlisted candidate during the selection process. 

Symbolic planning is a powerful tool to help AI agents determine high-level sequences of actions to move from an initial state to a goal state. It has successes in various practical domains such as robotic manipulation and autonomous navigation. However, it lacks the capability of dealing with novel environments without necessary domain and problem descriptions.

Some attempts have been made to tackle this issue, including using inductive logic programming or other learning methods to learn the domain knowledge and update the environment representation. These approaches usually need a certain amount of data and a long time to adapt to the new environment. In this project, you are expected to explore new methods that lead to a more efficient novelty adaption for a symbolic planning agent.

This research project can be extended, and supported with additional funding, beyond the standard duration (12 weeks) of the FRT program. This possibility and duration of extension will be considered on a case-by-case basis and discussed with the shortlisted candidate during the selection process. 

Graph neural networks (GNNs) have become a popular machine learning model for graph prediction tasks. Considerable progress has been made in exploring the connections between the representation power of GNNs and graph properties from the algorithmic perspective. This project aims to look into the recent progress of graph neural networks and benchmark several state-of-the-art GNNs in terms of their theoretically guaranteed graph properties, representational power, and empirical performance. 

Candidates with a strong background in machine learning and graph theory and strong programming skills are preferred. 

Graph Algorithms and Graph Neural Networks is a research area that provides fundamental and powerful ways of exploiting the structure of graphs. Recent advances in machine learning, particularly deep learning, are also achieving remarkable progress in a wide variety of application domains. Graph Research Lab aims to investigate graph-related problems by marrying the best of two worlds: traditional graph algorithms and new machine learning techniques to bridge the gap between combinatorial generalization and deep learning.

Recently, various attempts have been made to understand the connections between the representation power of GNNs and graph algorithms such as the Weisfeiler-Leman algorithm. Through these connections, a beautiful characterisation of GNNs by finite-variable logic has been established. Nonetheless, some interesting questions still remain under-explored, such as the locality of GNNs and first-order logic/finite model theory, the generalisation ability and the interpretability of GNNs, etc. This project aims to explore novel connections between graph algorithms and graph neural networks.

Candidates with a strong background in machine learning and graph theory and strong programming skills are preferred. 

Graph Algorithms and Graph Neural Networks is a research area that provides fundamental and powerful ways of exploiting the structure of graphs. Recent advances in machine learning, particularly deep learning, are also achieving remarkable progress in a wide variety of application domains. Graph Research Lab aims to investigate graph-related problems by marrying the best of two worlds: traditional graph algorithms and new machine learning techniques to bridge the gap between combinatorial generalization and deep learning.

Multimorbidity refers to the coexistence of multiple chronic health conditions in an individual and is a complex and multifaceted challenge in India. Implementing educational interventions as part of a broader strategy to manage and prevent multimorbidity could be a feasible option. This will be a rapid qualitative investigation including a few key informant interviews and a review of relevant policy documents.  

Background in policy analysis, review of policy documents, qualitative interview, and skills in qualitative data analysis using Atlas ti Or Nvivo software are required.

Dr Haribondhu Sarma

Analysis and Partial Differential Equations: Pierre Portal

Harmonic, stochastic, and/or functional analysis of PDE and SPDE. The specific project will be tailored to the scholar's experience and interest. 

This project is only available for undertaking to start in July 2024 onwards.

Assoc Prof Pierre Portal

Conduct a survey of recent results in the automorphisms of right-angled Coxeter groups, exploring the solution to the word problem in these groups.

Preferred - undergraduate level students.

Applicant should have taken a course in abstract algebra and a course in topology.  Some coding skills are desirable.

Assoc Prof Adam Piggott

Using mathematics for truth-telling in mathematics history; collection and investigations of sparse archival data on non-Western mathematics using phylogenetic and Bayesian methods and new AI tools; transmission of mathematics within and between cultures; decolonisation of mathematics.

The project would suit a student from an Indigenous minority background who is interested in non-Western and Indigenous mathematical knowledge.

Several of the mathematicians in Algebra/Topology at the Mathematical Sciences Institute will be willing to host projects at the interface of several algebraic and topological areas.  

The project will be tailored to the interests and background of the student.

A dipole is a simpler alternative magnetic confinement configuration that produces closed field lines.  In the laboratory, a dipole field can be constructed by levitating a superconducting magnetic coil. This project would compute the field by solving the Grad-Shafranov equation (the governing equation for the magnetic field) out to the vacuum vessel, and compute particle orbits and confinement. 

A background in computational science and modelling is desirable.

Develop a Physics Inspired Neural Network to solve for tokamak equilibrium, and compare it to analytic solutions.

A background in computational science and modelling is desirable.

In this project, the student will be introduced to one of the many areas of mathematics motivated and inspired by String Theory and Quantum Field Theory. This could be, but is not limited to, Dualities, Generalised Geometry, Conformal Field Theory, (bundle) Gerbes, Yang-Mills and Seiberg-Witten gauge theory, Gromov-Witten invariants, etc. and will involve mathematics such as Differential Geometry, Symplectic Geometry, Algebraic Topology, (infinite dimensional) Lie Algebras, Operator Algebras, and Vertex Operator Algebras.

The project will be tailored to the interests and background of the student.

Analysis of manifolds including harmonic maps, minimal surfaces and geometric flows.  Specific topics can be tailored to the student's background and interests.

This research project can be extended, and supported with additional funding, beyond the standard duration (12 weeks) of the FRT program. This possibility and duration of extension will be considered on a case-by-case basis and discussed with the shortlisted candidate during the selection process. 

In this project, we will explore some current research topics in representation theory and related areas through implementing computational packages in computer algebra systems such as SageMath. Prior experience with programming, particularly Python, is strongly recommended for this project. The precise mathematical topic chosen will be tailored to the interests and background of the student.

Prior programming background required. A background in Python is ideal, but any other programming language is fine. Ideally have taken at least two courses in abstract algebra.

Classical and modern topics in the geometry of algebraic curves and surfaces. The specific project will be tailored to the student's interests and background.

Note: PhD candidates will only be considered if they have the requisite skills.

Background in commutative algebra or algebraic geometry is highly desirable.

The Australian health workforce comprises a substantial representation of professionals from the Indian diaspora, and health workforce planning and optimisation is a bilateral health policy priority for India and Australia. This population health study uses quantitative methods to conduct secondary data analysis of Australian medical health workforce data to derive and understand key determinants of select work outcomes, such as working conditions, job satisfaction, family circumstances, etc. and scopes of comparable determinants of the Indian(medical) health workforce. The study outcome is a publishable journal paper to guide health policy bilaterally. ANU researchers lead this study with institutional collaborators for technical guidance towards successful outcomes.

About the supervisors: The supervisors have expertise in understanding health workforce challenges from a global and regional perspective.

 Background requirement: Postgraduate students with prior experience/education in public health and experience in research writing and data analysis are preferred. Basic to intermediate experience using SPSS/STATA for data analysis is preferred. The study would suit a public health student interested in developing applied and theoretical skills in the project area. A person who enjoys working in teams where individual responsibility, work autonomy and commitment to timely completion are expected. 

As part of the ANU medical school's award-winning medical education academic team, the research invites medical postgraduate students interested in medical education research and pedagogy. The research entails the co-development of novel artificial intelligence (AI) and traditional-based technology-enhanced medical education teaching pedagogies to enhance the delivery of undergraduate/postgraduate medical curricula, focusing on leveraging unique educational environments in Australia and India. As part of a larger capacity-building initiative, this research project would link a leading medical school in India to ANU SMP to support bidirectional research development and learning.

About the supervisors: The supervisory team has established credentials in medical education teaching innovations and possesses a contextual understanding of how Anatomy is taught in Indian and Australian medical schools. The supervisory panel would also invite a senior faculty member from the Indian host Institute for technical input during online meetings.

Background requirement: the research invites currently enrolled postgraduate students in medical school(s) with experience in using technology in teaching anatomy online and in person to undergraduate and postgraduate medical students. Cadaveric dissection skills would be preferred. 

Evaluation of the role of early additional cardiac assessments using electro-anatomical mapping (EAM) and EAM-guided endomyocardial biopsy in patients with newly diagnosed NICM, in predicting risk of sudden cardiac death and improvement or failure of improvement in cardiac function. Moreover, in patients needing CRT, research will evaluate the role of personalized lead placement in improving CRT response rate. 

Experience in cardiology and/or cardiac electrophysiology and/or cardiac imaging and/or heart failure is required.

Note: PhD candidates will only be considered if they have the requisite skills. 

For PhD candidates, the duration of this project can be extended to a total period of up to 3 years, supported by additional funding for extended living costs beyond the standard duration of the FRT program.     

Cells lives in an environment filled with viscous flowing fluid. We argue that extracellular fluid (ECF) properties not only control the rate of diffusion but also shape the physical forces that a cell experiences. It is therefore plausible that fluid mechanical forces precede other taxis. We will create new cell-based assays that can accelerate the micro-Avatars (organoid, spheroids) for human disease diagnosis and therapy.

Background in Cell culture, Microscopy Imaging, Imaging Analysis, Basic Biophysics or Biochemistry is preferred.

Note: PhD candidates will only be considered from IIT Madras or IIT Delhi and if they have the requisite skills.

Investigating how variants in genes involved in cytokine signalling pathways contribute to the pathogenesis of autoimmune diseases such as lupus.  We have developed unique mouse models that carry genetic variants from lupus patients. This project will examine whether genetic variants increase immune cell responsiveness to cytokines and what effects this has on cell activation and tolerance mechanisms.  

Background in general lab cellular and molecular biology techniques.  Experience with Flow cytometry is advantageous but not essential.  Must be willing to be involved in animal studies. 

This project will harness novel TLR7 inhibitors and examine their efficacy in vivo to prevent the generation of autoantibodies in auto-immune mouse models.  

Background in general lab cellular and molecular biology techniques.  Experience with Flow cytometry is advantageous but not essential.  Must be willing to be involved in animal studies. 

Modelling and interpretation of RNA molecules with deep learning for applications in RNA programming and therapeutic design. 

Background in machine learning, deep learning, and software development, with experience in applications in genomics or transcriptomics.

Personalised medicine in autoimmune disease ^

This project involves the identification and demonstration of gene variants contributing to immune dysfunction and autoimmune disease. We demonstrate how human mutation alters protein function, leading to disturbed immune responses, and therefore autoimmunity. Using human and CRISPR mouse models we identify new mechanisms of autoimmunity, ways to treat with personalised medicine, and create models of autoimmune/autoinflammatory disease.

Background in wet lab skills desired.

This research project can be extended, and supported with additional funding, beyond the standard duration (12 weeks) of the FRT program. This possibility and duration of extension will be considered on a case-by-case basis and discussed with the shortlisted candidate during the selection process. 

Assoc Prof Simon Jiang

Proton-boron fusion has the potential to deliver limitless clean energy. This project will aim to understand the physics underpinning this important nuclear reaction.

Background in computational physics, data analysis, and nuclear physics is required.

The project will involve writing high-performance computer code to simulate nuclear fusion using time-dependent coupled channel models.

Background in computational physics, data analysis, and nuclear physics is required.

Our group at the ANU hosts Australia's CYGNUS prototype detector, CYGNUS-1. A number of experimental and computational projects are available for students with an interest in this area.

Note: PhD candidates will only be considered if they have the requisite skills.

SABRE is an Australian dark matter experiment due to come online in 2023. Software development and computational/analysis studies are available.

Note: PhD candidates will only be considered if they have the requisite skills.

Experimental nuclear structure *

Fundamental and applied aspects of nuclear science at Australia's Heavy Ion Accelerator Facility. Projects use gamma-ray, electron and particle spectroscopy techniques to study atomic nuclei across a range of physics themes, including studies of the structure and shapes of atomic nuclei, nuclear lifetime measurements by direct timing and Doppler-shift methods, and magnetic moment measurement by hyperfine interaction techniques. 

Note: PhD candidates will only be considered if they have engaged in related nuclear physics research at any partner institution.

Dr AJ Mitchell, Prof Greg Lane, Assoc Prof Tibor Kibedi, and Prof Andrew Stuchbery

Understanding energy dissipation in colliding quantum many-body systems

The development, characterisation and optimisation of a new gas ionization detector system, with the aim to use this new system, and our 15 million Volt heavy ion accelerator, make precision measurements of the earliest stages of energy dissipation through the measurement of multi-nucleon transfer reactions, identifying the mass, charge and kinetic energies of nuclear reaction products.

Dr Kaitlin Cook, Prof Mahananda Dasgupta, and Prof David Hinde

The project aims to explore room-temperature Bose-Einstein condensates (BEC) made of hybrid light-matter particles, called exciton polaritons. These atypical BECs, which are inherently non-equilibrium due to its driven-dissipative nature, are largely unexplored at room temperature where thermal excitations are excitations are expected to play a dominant role compared to cryogenic conditions.

Background in optics, data analysis using matlab, python, or related scientific programming tools is required.

Note: PhD candidates will only be considered if they have the requisite skills.

This research project can be extended, and supported with additional funding, beyond the standard duration (12 weeks) of the FRT program. This possibility and duration of extension will be considered on a case-by-case basis and discussed with the shortlisted candidate during the selection process. 

Development of nanostructured optical metasurfaces for generation, transformation, and imaging of multi-photon quantum states.

Background in quantum optics and/or nanophotonics is desirable.

Calculation and optimisation of metasurface design for tunability with small stimulus and fast response.

This project will construct a 3D optical lattice apparatus for ultracold metastable Helium atoms, which will form an experimental quantum simulator to investigate quantum many-body physics. A range of experiments will be performed such as studying higher-order quantum correlations across the superfluid to Mott insulator phase transition.

This research project can be extended, and supported with additional funding, beyond the standard duration (12 weeks) of the FRT program. This possibility and duration of extension will be considered on a case-by-case basis and discussed with the shortlisted candidate during the selection process. 

This experimental project aims to create entangled states of ultracold helium atoms where the entanglement is between atoms of different masses. By manipulating the entangled pairs using laser-induced Bragg transitions and measuring the resulting correlations, we will study how gravity affects mass-entangled particles.

This research project can be extended, and supported with additional funding, beyond the standard duration (12 weeks) of the FRT program. This possibility and duration of extension will be considered on a case-by-case basis and discussed with the shortlisted candidate during the selection process. 

Antiparticles and antimatter have progressed from theory and science fiction to become an important and exciting area of pure and applied science. This fundamental atomic physics project will investigate how antimatter and matter interact by experimentally studying the interaction of positrons (the electron anti-particle) with trapped ultracold rubidium atoms.

This research project can be extended, and supported with additional funding, beyond the standard duration (12 weeks) of the FRT program. This possibility and duration of extension will be considered on a case-by-case basis and discussed with the shortlisted candidate during the selection process. 

Sensing of proteins by combining single-molecule solid-state nanopore analytics and machine learning.

Interest in interdisciplinary research at the interface of physics, chemistry and biology is desirable.

This research project can be extended, and supported with additional funding, beyond the standard duration (12 weeks) of the FRT program. This possibility and duration of extension will be considered on a case-by-case basis and discussed with the shortlisted candidate during the selection process. 

The project aims to develop novel approaches to generate high harmonics – source of light with extremely short wavelengths in vacuum-ultraviolet and extreme-ultraviolet ranges. Currently, such sources are large and expensive. However our recent research suggests practical all-solid-state sources are feasible to develop with the concepts of nanoresonators and metasurfaces. Such sources would increase the resolution of optical microscopy and metrology. Conventional optics can study objects with sizes down to about ten-millionth of a metre, which is limited by the wavelength light sources. However contemporary nanotechnology research and industries create a demand for optical diagnostics of much smaller objects – down to one billionth of a metre. We aim to meet this demand with new ultra-short wavelength light sources based on high harmonic generation in nanostructured solids.

Researchers joining the project can be involved in one or more of the following lines of investigation:
(1) Supercomputer simulations of the process at the atomic level.
(2) Computations based on classical electrodynamics;
(3) Clean-room nanofabrication of samples;
(4) Optical experiments with nanostructured samples

As a highly promising technology to support ultra-fast connectivity in the 6G and beyond era, terahertz (THz) communications (0.1-10 THz) have recently attracted rapidly growing attention from academia and industry. In this project, the student aims to design new communication strategies and signal processing algorithms for enabling intelligent THz communications for wireless systems in the 2030s.

Undergraduate applicants are expected to have
(i) solid background in communications and signal processing,
(ii) high-level programming skills (such as the ability to write numerical simulation programs in MATLAB or equivalent and/or machine learning programs in Python or equivalent),
(iii) high motivation and good self-study capabilities,
(iv) excellent written and verbal communication skills, and (v) good interpersonal skills.

Additional note: All eligible Indian institutions where the candidates meet the following expertise expectations:
(i) solid background in communications and signal processing,
(ii) high level programming skills (such as MATLAB and/or Python), and
(iii) excellent publication record (such as first-authored publications in IEEE journals/letters).

Extreme events (e.g., bushfires, floods and droughts) can influence the source and transportation of pollutants, posing substantial risks to water security. This research aims to understand how water quality responds to extreme events, and how these responses vary by catchment conditions. The study will generate important management implications to sustain the supply of clean water under a changing climate.

The research project duration can be extended - subject to approval.

Candidate must meet the following requirements: 

1. Background in a relevant field (environmental science or environmental engineering) and demonstrated relevant experience in a research or research support role in a related discipline and an interest in a field closely related to allocated research activities.
2. Sound knowledge of quantitative and qualitative research methodologies. Experience in managing and analysis of high-volume research data may be regarded positively.
3. Demonstrated effective interpersonal skills and verbal and written communication skills. 
4. Proven organisational skills and attention to detail, with a demonstrated ability to prioritise own workload and to work effectively both independently and as part of a team.   
5. Demonstrated experience using information systems, including the ability to generate complex reports and demonstrated skills using the MS Office suite, in particular Excel.
6. Programming experiences (e.g., R, Python) are preferred. 

For the suitable candidate, the duration of this project can be extended to a total period of up to 6 months, supported by additional funding for extended living costs beyond the standard duration of the FRT program.

Design and create functional catalysts through commercially viable methods for electrochemical reactions.

Backgrounds in materials science and chemistry are required.

For the suitable candidate, the duration of this project can be extended to a total period of up to 6 months, supported by additional funding for extended living costs beyond the standard duration of the FRT program.

Dr Ehsan Nabavi