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analytical imaging methods, then working with collaborators to apply these methods to biomedical research, diagnostic imaging and beyond. Research projects vary from purely theoretical, to computational
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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 insulators and Weyl semimetals. The former favours quantum states of matter (e.g. excitonic...
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My interests span a wide range of topics in theoretical physics, including: geometric phases, topological defects in matter and radiation fields, inverse problems (scalar and vector tomography), singular optics, using electrons, atoms and light and the exploration of complex systems using...
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-class honours (H1) Bachelor’s degree or equivalent in the relevant research area (completed or near completion) have applied for admission to a PhD program at an Australian university or have completed
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Family Foundation. The scholarships are intended to supplement an existing Australian Government Research Training Program Stipend Scholarship (RTPS) or similar institutional PhD stipend scholarship
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My research interests focus on the stars - primarily their structure, evolution and nucleosynthesis. This can involve modelling of mixing in stars, or effects of changing nuclear burning rates; trying to understand why certain elements are more abundant than others; or how the different...
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My research focuses on the theory of strongly correlated phenomena in cold atomic gases and electron systems. Particular topics of interest include low-dimensional quantum systems, superconductivity and quantum impurities. I was previously part of the Australian Centre of Excellence for Future...
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I am an ARC Future (former DECRA) Fellow and lead the Structured Nanophotonics Group at Monash University. My research in nanophotonics explores the full potential and multi-dimensional nature of light, focusing on controlled light-matter interactions at the nanoscale. Driven by the fascinating...
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Machine Learning for Image Classification. Eligibility You must: We would like you to have: sound knowledge of machine learning, computer vision and image processing strong programming skills. How to apply
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computational while other work will involve time spent in the lab. Search for physics beyond the Standard Model in penguin decays in data from the LHCb experiment. Identify particle identification requirements