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university Advance transdisciplinary scholarship through research, collaboration and high-impact practice Engage with regional communities in the development of community-led flood intelligence networks
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opportunity The University of Sydney is seeking a Postdoctoral Research Associate/Fellow to join a flagship, industry-funded research program advancing carbon-neutral energy systems modelling for Australia’s
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 3 months ago
high-impact practice Engage with regional communities in the development of community-led flood intelligence networks Position overview This fixed-term position will be based at the School of Art and
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criteria A PhD in Computer Science or Software Engineering or Computational Statistics, or a related field; or a Master’s qualification in a relevant field and/or equivalent demonstrated experience
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for drug discovery. Publishing peer-reviewed research and contributing to industrial software tools. About You To be successful in this role, you will have: A PhD in machine learning, computer
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modelling, including two-phase flow in fractures, stochastic permeability analysis, and upscaling to fracture networks. Deploy large scale simulations using high-performance computing (HPC) and collaborate
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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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Oct 2025 - 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 position within
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salary and 17% Superannuation Based at one of the RMIT’s Melbourne campuses (City, Brunswick or Bundoora) About the Program Each year, RMIT brings on the world’s best and brightest researchers and teams
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are looking for - Selection Criteria: Essential: A PhD in a relevant discipline such as Applied Statistics, Mathematics, Bioinformatics, and/or Computational Genetics, Data Science. A demonstrated track record