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MACQUARIE UNIVERSITY - SYDNEY AUSTRALIA | North Ryde, New South Wales | Australia | about 1 month ago
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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across large cohorts (e.g., >300 samples) demonstrated experience in data analysis, visualisation, and machine learning, using programming languages such as R or Python excellent interpersonal, verbal, and
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monitoring approaches (e.g., machine learning, real-time sensing). Sponsorship / work rights forAustralia You must have unrestricted work rights in Australia for the duration of this employment to be eligible
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years. This role will develop and apply new machine-learning based approaches for extremely precise radial velocity studies and exoplanet spectroscopy with the NEID, HPF, and MARVEL facilities, and pursue
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-platforms-lab . About You (Selection Criteria) You are a motivated and collaborative early career researcher with a strong foundation in AI and machine learning, and a genuine enthusiasm for applying
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to interact professionally with participants, team members, and external stakeholders attention to detail and accuracy in data collection, entry, and management competence in basic computer applications (e.g
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the key focus areas: Emerging track record and recognition for quality research outputs in the field of biological mathematics. Demonstrated mathematics and computer programming skills with experience in
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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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the key focus areas: Emerging track record and recognition for quality research outputs in the field of biological mathematics. Demonstrated mathematics and computer programming skills with experience in
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the key focus areas: Emerging track record and recognition for quality research outputs in the field of biological mathematics. Demonstrated mathematics and computer programming skills with experience in