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outputs of a team dedicated to translating discovery into meaningful impact for people living with Friedreich Ataxia. We are seeking someone with a PhD in computer engineering, biomedical engineering
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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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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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Adaptation who has: a PhD in a relevant field such as Management, Organization Studies, Urban Studies, Social Sciences, Political Sciences, Computer Sciences, or Engineering, with a strong track record
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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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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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strategic planning initiatives to improve research culture and direction. About you: A PhD in Medical Physics, Physics, Engineering, Computer Science, or a related discipline Expertise in real-time motion
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 3 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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PRIMARY DETAIL Lead cutting-edge ARC-funded research on butterfly behaviour and visual ecology at Macquarie University! - Salary package: Level A - Step 6 (PhD awarded rate) $109,272 p.a., plus 17
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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