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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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agents. Your research will explore how reinforcement learning, multi-agent cooperation and generative worldmodels can deliver adaptive strategies that thrive amid volatile, multi-asset markets, micro
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to supplement a scholarship. Learn more about Mark Govier and why he created this scholarship
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materials systems at the molecular level with machine learning. The PhD Student will undertake a study analysing mass spectral imaging data streams in real time using machine learning workflows. A pathway for
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International students Find support, advice and what to expect living and studying as an international student at the University of Melbourne. Learn more How can we help? Find a scholarship View scholarship guide
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at the University of Melbourne. Learn more How can we help? Find a scholarship View scholarship guide FAQ Contact us
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learning by using Bayesian learning principles. Among other things, Bayesian learning gives AI systems the ability to quantitatively express a degree of belief about a prediction or statement. By bridging
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at Melbourne International students Find support, advice and what to expect living and studying as an international student at the University of Melbourne. Learn more How can we help? Find a scholarship View
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into fundamental molecular events. At the same time, access to translational pipelines will enable the candidate to apply their learnings in a meaningful way, revealing novel therapeutic targets critical for cancer
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research in the field of sustainable housing. Assisting the organisation in developing a cutting-edge, AI-driven platform for home retrofitting digital products. Learning about the integration of AI with