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information about this opportunity, please contact Professor Ian Godwin, Director, Centre for Crop Science at i.godwin@uq.edu.au . For application inquiries, please reach out to the Talent Acquisition team
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Perinatal Epidemiology and Statistics Unit (NPESU) in the Centre for Big Data Research in Health. Some key skills and experience required: A PhD in biostatistics, epidemiology or applied statistics, or a
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Criteria: A PhD in applied mathematics, engineering, computer science, data science, physics, or a related area. Strong academic track record (including peer-reviewed publications and conference
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Salary package: Level A - Step 6 (PhD awarded rate) $109,272 p.a., plus 17% employer's superannuation and annual leave loading. Appointment Type: Full-time, fixed term appointment until 17 December
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31 Oct 2025 Job Information Organisation/Company MACQUARIE UNIVERSITY - SYDNEY AUSTRALIA Research Field Biological sciences Researcher Profile Recognised Researcher (R2) Established Researcher (R3
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 4 days ago
PhD in seismology, geophysics, computer/data science, or planetary science. You will have demonstrated expertise in global seismology, particularly relating to the Earth’s core, core–mantle boundary
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School of Earth Sciences Full-time appointment on a fixed term basis for two years. Base salary range: Level B, $118,150 – $139,812 p.a. plus 17% superannuation. About the area The School of Earth
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School of Earth Sciences Full-time appointment on a fixed term basis for two years. Base salary range: Level B, $118,150 – $139,812 p.a. plus 17% superannuation. About the area The School of Earth
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: Completion or near completion of a PhD in Synthetic Biology, Molecular Biology, Bioengineering, or related discipline. Demonstrated expertise in microbial strain engineering. Experience with cloning, genome
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geometry, and/or data science. Specific topics of focus include, but are not limited to, linear response, random and nonautonomous dynamical systems, spectral analysis, machine learning, data-driven dynamics