32 parallel-programming-"Multiple"-"Simons-Foundation" research jobs at University of Adelaide
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Wildlife Crime Research Hub as part of the ARC Industry Laureate Fellowship program, Combatting Wildlife Crime and Preventing Environmental Harm at one of Australia’s leading research institutions
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responders and operational risk assessment regarding skin decontamination and will build on a program of work focused on dermal exposure to chemicals. To be successful you will need: Completion of a PhD in
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environment The University is a uniquely rewarding workplace. The size, breadth and quality of our education and research programs - including significant industry, government and community collaborations
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, Health Sciences, Nursing, or a related field. Strong communication and computer skills (e.g. MS Office, Redcap, data management/analysis programs and other electronic communications). Experience working
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prevention. The successful candidate will join the Wildlife Crime Research Hub and work as part of the ARC Industry Laureate Fellowship program, Combatting Wildlife Crime and Preventing Environmental Harm
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agriculture with appropriate industry experience Demonstrated research excellence in plant physiology, plant molecular biology, phylogeny, molecular evolution, bioinformatics, multi-omics, and programming
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peer-reviewed literature An interest in global change ecology, macroecology, biogeography, or conservation biology Strong computational and analytical programming skills A good knowledge of advanced
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policy audiences. Proficient with Microsoft Office programs, including Microsoft Word, Microsoft Excel, Microsoft Powerpoint. **This position requires a National Police Clearance and a Defence related
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Capability is a $250 million enterprise powered by UoA and UNSW, with funding from the Australian Government through the Trailblazer Universities Program, as well as university and industry partners. Our
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Learning-related field. Programming experience in Matlab, Python, C++ or other relevant language and experience in deep neural networks. Experience and demonstratable knowledge in deep learning, transformer