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PhD student(s) will join a vibrant team of postdocs, academics, and up to four PhD students working collaboratively across modelling, qualitative fieldwork, and optimisation techniques. PhD Research
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deep learning theory, Bayesian statistics, and generative modelling, this work will advance our understanding of both the capabilities and vulnerabilities of modern AI systems. This will have potential
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through theory and simulation and/or experimental design and testing; developing new image reconstruction algorithms for providing more information with less radiation; and applying our techniques
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the structure present in food systems dictates functional aspects such as digestion and release of nutrients. Working alongside other postdocs and students focused more on biological aspects of these processes
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to provide child and aged care and companionship. Expected outcomes include an improved understanding of anthropomorphised robots in everyday life and innovation in home helper robot theory and
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collaborations with local and international research groups such as the European X-Ray Free-Electron Laser Facility in Germany. Student projects may focus on physics theory, algorithm development, experimental
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), singular optics, using electrons, atoms and light and the exploration of complex systems using statistical field theory. "Catastrophes on order-parameter manifolds" (with Dr Alexis Bishop and Dr Timothy
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. Depending on your interests, research projects can range from developing new ways to ‘see’ atoms to understanding technologically-important materials. They can involve theory or experiment or a mix of both
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My area of expertise is condensed matter theory. I am interested in the interplay between interactions and unconventional electronic properties of novel materials including graphene, topological
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Fellowship at LMU Munich, and a postdoc position at RMIT University. My nanophotonics research seeks to uncover the underlying physics in structured light-matter interactions at nanoscale. We aim to develop