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numerical modelling framework to simulate how light and heat interact with the target body tissue, while also incorporating neural signalling dynamics to explore how light-based stimulation affects
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. This position will focus on one key stream: understanding and improving the interaction between EVs and roadside barriers. This will involve: Modelling EV crash dynamics with conventional and SRB barriers
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, especially in ultracold quantum gases or condensed matter theory Proven analytical, computational, and modelling skills Experience with numerical simulations of quantum or many-body systems A deep curiosity
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mechanisms and transformer models. Qualifications Bachelor’s degree with First Class Honours (or equivalent) and/or a research master’s degree in computer science, AI or Computer Vision; or an equivalent
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nanoparticles in drug delivery or diagnostics, familiarity with cellular targeting, and use of computational tools to model nanoparticle behaviour. Experience in a regulated research environment is also
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, especially in ultracold quantum gases or condensed matter theory Proven analytical, computational, and modelling skills Experience with numerical simulations of quantum or many-body systems A deep curiosity
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to peer-reviewed academic publications Qualifications Completed undergraduate degree in physics, computer science, machine learning, computational modelling, or similar. About Swinburne University
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the Collaborative Research Centre for Low Carbon Living. The project uses agent based modelling (ABM) to represent consumer behaviour, social networks and their responses to non-financial incentives and barriers in