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Research Fellow in Computational Neuroscience Job No.: 686523 Location: Clayton campus Employment Type: Part-time, fraction (0.7) Duration: Fixed-term appointment until 30 November 2026 Remuneration
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5 Jan 2026 Job Information Organisation/Company University of Melbourne Department School of Computing and Information Systems Research Field Computer science » Cybernetics Engineering » Mechanical
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imaging. Within our research program, you will perform grant funded research developing novel algorithms or building new dynamic imaging systems that account for patient motion (breathing, cardiac, etc
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) Application Deadline 19 Feb 2026 - 00:00 (UTC) Country Australia Type of Contract Other Job Status Part-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the
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program, you will perform grant funded research developing novel algorithms or building new dynamic imaging systems that account for patient motion (breathing, cardiac, etc.) during medical imaging and
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initiatives, securing competitive research funding, and establishing industry links. Qualifications A PhD degree in Computer Science related field is desirable. Please Note: Appointment to this position is
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) Application Deadline 17 Feb 2026 - 00:00 (UTC) Country Australia Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 9 days ago
international leadership and innovation, focused on developing new methods, whether experimental, analytical or computational. Our research spans the range from solid earth evolution to climate processes, and
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Application Deadline 1 Feb 2026 - 00:00 (UTC) Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff
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qualification in a relevant discipline (e.g. astronomy, astrophysics, physics, or computer science). Demonstrated relevant subject/discipline knowledge and knowledge and experience in relevant research techniques