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will commence with, in parallel, the survey for collecting the data and a comparison of machine learning methods on artificial pseudo-randomly generated data. The world will see all too many changes
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will commence with, in parallel, the survey for collecting the data and a comparison of machine learning methods on artificial pseudo-randomly generated data. The world will see all too many changes
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machine/deep learning, computer vision, or applied statistics. Solid programming skills in Python and experience with deep learning frameworks (e.g., PyTorch or TensorFlow) Project funding Other Funding
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machine vision species classification, web scraping, environmental DNA, satellite imagery) and agent-based models and ecological simulations. Our recent work, funded by the Monash Data Futures
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trapped within a deformable, yield-stress material. Working alongside a co-supervised PhD student and the wider investigator team, you will build and extend simulation tools to explore droplet
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Primary supervisor Aamir Cheema Co-supervisors Charith Jayasekara Research area Software Systems and Cybersecurity This PhD project focuses on the design and evaluation of hybrid quantum–classical
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Primary supervisor Aamir Cheema Co-supervisors Charith Jayasekara Research area Software Systems and Cybersecurity This PhD project focuses on the design and evaluation of hybrid quantum–classical
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fluid migrates, spreads and becomes trapped within a deformable, yield-stress material. Working alongside a co-supervised PhD student and the wider investigator team, you will build and extend simulation
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excellent academic record in computer science, economics or a cognate field. An Honours degree with H1 or equivalent is required for Graduate Research admission. An interest in game theory and in how
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excellent academic record in computer science, economics or a cognate field. An Honours degree with H1 or equivalent is required for Graduate Research admission. An interest in game theory and in how