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Research Fellow - CONNECT Consumer Program - Australian and New Zealand Intensive Care Research Centre (ANZIC-RC) Job No.: 687556 Location: 553 St Kilda Road, Melbourne Employment Type: Part-time
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Acknowledgment of Country Australia's Chief Scientist and the Office of the Chief Scientist recognise the first peoples of this nation and their ongoing cultural and spiritual connections to the lands, waters, seas, skies, and communities. We acknowledge First Nations peoples as the Traditional...
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Fellow, with expertise in psychology and computer science, to join our world-leading School of Psychology to support research on an ARC Laureate Project, Transforming Understanding of Cognitive Ageing
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | about 1 month ago
& PEWER_Level B_Research Fellow_SOCO_CSS_2026.pdf Opportunity to work on a high-impact Defence-funded research project under the ASCA Emerging and Disruptive Technologies program. Develop cutting-edge AI planning
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origin of imperfections within Josephson junctions and the ramifications for quantum computing. This work is part of a multi-institution project involving RMIT, Rigetti Computing, Lawrence Livermore
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them The Opportunity Reporting to program co-leads Associate Professor David Slucki and Dr Susan Carland, the focus of this role will be to provide dedicated academic research support to the Monash
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· Part time fixed term until 2 March 2027 · Research Fellow role supporting research program in skin cancer prevention and treatment for high‑risk populations-including high risk kidney
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recognition for quality research outputs in the field of biological mathematics. Demonstrated mathematics and computer programming skills with experience in modelling infectious disease dynamics, population
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exposed to laser-accelerated intense proton beams. Primarily, the tasks are to be done by means of analytical calculations and high-performance computing simulations in a strong link with the industrial
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Future Fund–supported program (2026–2030) to reduce addiction, self-harm, and mental ill health. The project integrates 20 years of binational cohort and cross-sectional data with administrative datasets