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You For Level A Applicants will have completed or be near completion of a PhD in quantitative genetics, animal breeding, computational biology, or a related field. Additionally, you will demonstrate
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. Qualifications and requirements A PhD in Engineering or Computer Science with relevance to the outlined research area. A first degree in Engineering with research experience in creating digital twins or digital
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the Environmental Economics team. About the opportunity Research Fellow Biodiversity and Climate Change Adaptation will conduct research to support key deliverables for a National Environmental Science Program (NESP
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School of Health and Rehabilitation Sciences / Metro North Health Full-time, fixed-term position for 3 years Base salary will range from $137,542 - $181,934 (Academic Level C or D) + 17
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | about 2 months ago
research and deliver a research-led education program that encompasses the breadth of the sciences, supported by extensive international networks and by world-class facilities. To find out more about the
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Prof Christian Barry, RSSS Director on the Rio Tinto for Future Materials Contribute to a worldwide project Part-time position Position overview The Research School of Social Sciences invites
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | about 2 months ago
. Staff and students within the ANU College of Science and Medicine conduct research and deliver a research-led education program that encompasses the breadth of the sciences, supported by extensive
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) Based at our Herston Campus . About This Opportunity Join a nationally significant program driving innovation in clinical trial methodology at one of Australia’s leading research institutions
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Faculty of Science / School of the Environment Full-time fixed-term position through to mid 2028 Base salary will be in the range $82,057.75 - $109,246.18 (Academic Level A) and $114,824.05
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-renewable-energy-engineering Skills & Experience: A PhD in Computer Science or a related field. Thorough theoretical background in machine learning and deep learning. Demonstrated experience in developing