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Field
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Role type: Full-time ; Fixed-term for 2 years Faculty: Science School: School of Mathematics and Statistics, Melbourne Integrative Genomics (MIG) Salary: Level A.4 - A.6 AUD $100,214 - $108,156
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algorithms in the electromagnetic context. Qualifications and personal qualities: Applicants must hold a master’s degree (or equivalent) in geophysics or a closely related field such as applied mathematics
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statistics, physics, computer science, artificial intelligence, or a related quantitative field Experience with mathematical/statistical modeling and/or machine learning/Al methods Strong interest in
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an outstanding young talent in condensed matter theory to engage in cutting-edge projects in the field of quantum computing broadly defined involving research groups within the NCCR SPIN. The ideal NCCR Fellow has
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Development Lead. You will be responsible for contributions to a major new programme of research investigating ethical questions and public views concerning research using post-mortem brains. The project
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public engagement. This is a unique opportunity to contribute to a nationally significant research program with real-world impact. If you are passionate about environmental science and ready to take the
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geophysics or a closely related field such as applied mathematics or theoretical/computational physics. Master’s students may apply if they expect to complete their final examination by 01.10.2025. Employment
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outcomes through conferences, seminars, and public engagement. This is a unique opportunity to contribute to a nationally significant research program with real-world impact. If you are passionate about
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highly numerate subject (e.g. engineering, mathematics, physics, chemistry, statistics, econometrics, computer science, climate science) is advantageous. For Research Fellow and Senior Research Fellow
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Qualifications* PhD Degree in Engineering, Computer Science, Data Science, Applied Mathematics, Statistics, or a related field Familiarity with (biomedical) signal processing Experience working with clinical data