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experience in: Radial velocity, stellar, and/or exoplanet spectroscopy studies; and/or astronomical instrumentation or observing programmes Machine learning in physical science, using Jax, PyTorch, and/or
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agricultural science with a quantitative focus (or an equivalent discipline) expertise in statistical and machine learning approaches, with the ability to apply advanced methods to complex environmental and
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density) influence energy dissipation develop mathematical models to predict and explain these effects collect and analyse data, including with the use of machine learning use this knowledge to design
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students within the discipline, fostering a supportive and collaborative learning environment. Contribute to administrative activities and actively participate in School and Faculty meetings and initiatives
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of A/Prof Patrick Burr, please visit https://www.patrickburr.com/group At UNSW, you will join a vibrant materials research community within the School of Mechanical and Manufacturing Engineering and the
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seeking applicants with experience in: Radial velocity, stellar, and/or exoplanet spectroscopy studies; and/or astronomical instrumentation or observing programmes Machine learning in physical science
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collection and management for research, as well as basic knowledge of both quantitative and qualitative data analysis principles. Demonstrate high levels of computer literacy, including proficiency in learning
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collection and management for research, as well as basic knowledge of both quantitative and qualitative data analysis principles. Demonstrate high levels of computer literacy, including proficiency in learning
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For further information about this position, please contact Madeline Green, Research Fellow Molecular Fisheries Ecologist on Madeline.Green@utas.edu.au Please visit https://www.utas.edu.au/jobs/applying
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contributions to the University. See how we lead in flexible work to enable an outcome focused and inclusive workplace. To learn more about our culture and hiring process, visit our Jobs at Macquarie page. Why