This project uses Geant4 simulations to investigate how naturally occurring cosmic rays interact with materials relevant to physics and environmental research, including NaI(Tl) crystals, gaseous detectors, and soil.

Radioactivity from radon is a leading background for dark matter and other rare-event physics experiments. Developing ultra-sensitive radon detection is crucial to improve discovery potential and enable the next generation of breakthroughs in fundamental physics.

This project investigates radon-induced backgrounds in the CYGNO directional dark matter detector. The student will develop an event-by-event simulation of radioactive decay chains and use alpha particle signatures to infer low-energy backgrounds, contributing to the understanding of detector performance using recent experimental data.

This project will allow us to understand the time-dependence of quantum tunnelling and nuclear fusion.

Directional dark matter searches provide a way to probe beyond the irreducible ‘neutrino fog’ that limits traditional dark matter experiments. CYGNUS-OZ is part of the global directional dark matter effort, and this project focuses on the critical challenge of radon control in these detectors.

Proton-boron fusion has the potential to deliver limitless clean energy. This project will aims to understand the physics underpinng this important nuclear reaction by developing machine learning approaches to analyse complex reaction probabilities.

Experimental, simulation, and data analysis projects are available to help develop advanced detection technology which will form the basis of a future large particle physics experiment in Australia