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applied mathematical modelling machine learning multi-fidelity modelling numerical methods. Demonstrated programming ability (MATLAB/Python/C++) and enthusiasm to learn PyTorch. Previous experience in one
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Investigator, this role is part of a leading AI research group specialising in reinforcement learning and intelligent systems. The team is focused on producing world-class research while collaborating with
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. Desirable Strong problem-solving and self-learning abilities. Strong research interest and teamwork skills. Research article publication. How to apply Apply for this scholarship at the same time you apply
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Applications are open The PhD project is part of a collaborative project: ‘A “virtual market” for analysing the uptake of energy efficiency measures in residential and commercial sectors’, funded by
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collaboration and deliver practice-based research to address domestic, family and sexual violence in NSW. This initiative delivers on the NSW Government’s Domestic and Family Violence Plan creating safer
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the perceived enablers and constraints within different organisational and cultural settings. Second, drawing on these findings, the project will work collaboratively with coaches, sporting
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materials systems at the molecular level with machine learning. The PhD Student will work with tumour sections to develop multiple instance learning and weak supervision / spatial transcriptomics models
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. • be located at the agreed project location(s) and, if required, comply with the university’s external enrolment procedures. Selection criteria Skillset: Proficient in Python, machine learning, and
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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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explores how people of different ages play together, focusing on the experiences and perspectives of all participants. Working within a broader research program, the candidate will collaborate with