Available projects

There are a variety of projects available to students across areas in applied mathematics, physics, engineering, data science, and more. Please see below for details.

Numerical solution and simulation of electron transport and plasma models in various application areas

This project centres around construction of simulation frameworks for a variety of high impact plasma and electron transport applications, such as atmospheric lightning discharges, low temperature plasma-solid interactions through to magnetically confined fusion plasmas. Areas of investigation can be tailored to candidate expertise & interests, including numerical solution techniques for transport equations, the closure problem, machine learning and AI in computational science, kinetic or Monte Carlo methods.

Plasma modelling and simulation for magnetically confined fusion plasmas

A variety of projects are available in different modelling areas, with the focus applied to modelling a variety of important physics scenarios important to tokamak plasmas, such as those anticipated in ITER. Equilibrium plasma discharge, tokamak disruption, runaway electrons, edge-plasma, and surface wall interaction applications are examples of focus applications.

Formulation and application of deep learning and other AI techniques to physical sciences

The current wave of deep learning and AI research has yielded many advances in how tools such as neural networks, optimization, or uncertainty quantification can be used to improve modelling capability for a number of useful applications. Projects are available in the development of robust and transparent machine learning and AI techniques that can be employed to augment existing computational modelling techniques (e.g. surrogate models, reduced order models, etc) or to provide new avenues of solution (e.g. PINNs as a famous example).

Modelling of astrophysical relativistic electron jets from black hole accretion disks

Ultrafast jets of matter burst from dense accretion disks of massive black holes. High energy x-rays are observed, but there are many open questions on the origins of the observations. Recent developments in the understanding of how different electron collision processes impact the formation of relativistic electron populations may yet be added to existing models to improve the description and understanding of the black hole jet physics to help better understand the nature of these complex astrophysical systems.

Improving models of plasma populations and radiation in astrophysical bodies

This project is aimed at enhancing the modelling of ion populations in astrophysical plasmas over broad scales of temperature and density, such as those found in solar and other stellar atmospheres. This will help provide better modelling capacity to understand complex plasma environments, such as those found near the surface of our Sun or plasma clouds around active galactic nuclei.

Data analysis and exploration for the next-generation of cricket metrics

Using robust data science, mathematics, and statistics methods this project seeks to explore new ways to think about data science and performance metrics that can be built from player and team data in different forms of cricket. This project seeks to develop and explore ways of handling cricket player data, building fit-for-purpose metrics, and testing metrics against a mathematical and statistical inference framework to assess the validity of assumptions and strength of proposed metrics. This project features collaboration with Queensland Cricket in Albion, QLD.

Data science and deep learning towards unfolding Australian election and socioeconomic scenarios

This project seeks to use robust data science and deep learning methods to develop novel approaches to analysing and forecast a variety of political and socioeconomic scenarios. A recent example has been development of a deep learning framework for data acquisition, handling, and subsequent forecasting of election-night results based on historical trends and outcomes. A variety of research questions, data sets, and topics of research are available, with suggestions or proposals welcome.