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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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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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arts, languages, and social sciences, encouraging innovative studies that bridge traditional disciplines. Our faculty operates across six schools and five campuses, delivering programs from undergraduate
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We live and work in a world of complex relationships between data, systems, knowledge, people, documents, biology, software, society, politics, commerce and so on. We can model these relationships
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, with an operational footprint globally, the Maintenance Technology Institute (MTI) is a commercially orientated, professional research and engineering organisation that has been providing professional
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multidisciplinary in nature, cutting across statistics, econometrics, operations research and data science. Specific project outcomes relate to multiobjective optimisation, expected shortfall and conformal inference
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for Earth" grant by Microsoft, one of only 6 projects in Australia to receive this recognition. The new project will build original frameworks for future applications of Machine Learning and Computer Vision
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implementation science. We are now seeking an exceptional Research Fellow (Level B or C) to lead innovative methodological research in statistical theory for adaptive variants of longitudinal cluster randomised
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scholarship value Up to $30,000 Number offered Three See details Chau Yee Gan Pharmacy and Pharmaceutical Science International Merit Scholarship I am truly honoured to receive this scholarship, which greatly
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The world is dynamic, in constant flux. However, machine learning typically learns static models from historical data. As the world changes, these models decline in performance, sometimes catastrophically so. This PhD will develop technologies for addressing this serious problem, building upon...