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Faculty of Engineering, Architecture and Information Technology / School of Electrical Engineering and Computer Science Full-time fixed-term position for up to 12 months Base salary will be in the
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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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computer programming background who has an interest in ecology and biodiversity conservation, or an ecologist with computational modelling experience (e.g., using R, Python, Matlab). Project funding
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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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purpose to inspire Australia’s future change-makers and create a better tomorrow. Work that matters You will bring strong theoretical and practical expertise in Computer Science, Electrical Engineering or
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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
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analysis, including using AI/computer vision tools Experience with R or Python for data analysis Experience designing and conducting laboratory-based animal behaviour studies Experience in writing papers
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Full‑time, 3-year fixed term opportunity with potential to extend Join the Snow Vision Accelerator to drive a new research and drug‑development initiative at the University of Sydney’s School of