30 assistant-professor-and-human-computer-interaction Postdoctoral positions in Australia
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to develop their research expertise relevant to their particular field of study. The Senior Research Associate/Post-Doctoral Fellow will report to the Professor of Orthopaedic Surgery, St George Clinical
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Doctoral Scientist position. This position will report to Professor Jose Polo, Lead of the Cancer Epigenetics Program at the South Australian Immunogenomics Cancer Institute (SAiGENCI) and the Inaugural
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undertaking independent and or team research on Scientia Professor Buckley’s Australian Research Council (ARC) Laureate Research Program entitled “The Financial Data Revolution: Seizing the Benefits
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electronics and a strong passion for developing space payloads and collaborating on space projects with external partners, including space agencies. This position is part of a team led by Professor Paulo de
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) Sydney, in partnership with ANSTO (Australia), Imperial College London (UK), and Tokamak Energy (UK), is launching a groundbreaking research program focused on developing new materials for compact tokamak
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$101,332 to $113,918 Fixed term (2.5 years), Full-time, Joondalup Campus Open to candidates with relevant work rights POST DOCTORAL RESEARCH FELLOW (ARTIFICIAL INTELLIGENCE) COMPUTING AND SECURITY
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Employee Assistance Program For more information check out our benefits page! Your New Team – “ARC Centre of Excellence for Transformative Meta-Optical System“ https://www.tmos.org.au/work-with-tmos/ TMOS
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participation in conferences and workshops, and your active engagement with industry partners. This role reports to Associate Professor Ailar Hajimohammadi, and has no direct reports Level A, Salary - $110,059 to
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Research Associate in Medicinal Chemistry to work on an NHMRC funded project with Professor Peter Rutledge, Professor Richard Payne , and Dr Jessica Zhong , in collaboration with Professor Warwick Britton
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-carbon electric power systems, taking into account wake interactions between individual wind turbines. The project focus is on how to generate and utilize reduced-complexity predictive models for windfarm