12 algorithm-development-"Multiple"-"Prof" "UNIS" Postdoctoral positions at University of Sydney
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responsibilities will be to: conduct high-quality research in intelligent sensing and control for complex project environments develop and implement AI-based algorithms (e.g., GNNs, deep reinforcement learning
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Claire O’Callaghan, the successful candidate will join a collaborative, interdisciplinary team, where they will be supported to develop their own research questions and lead projects. Experience in
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multiple spatial and temporal scales. The PDRA will be based in the Geocoastal Research Group within the School of Geosciences at the University of Sydney. The School of Geosciences is a dynamic, collegial
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activities. The Sydney EarthBank node will join the national AuScope Geochemistry Network , an Australian consortium of Earth Science institutes cooperating to develop national geochemistry research
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from molecules to medicines, from patient to policy across a range of therapeutic areas. The Postdoctoral Research Associate applies and develops their expertise in conducting research to further
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research, scholarly or professional activity, independently or as part of a team, contributing to discipline knowledge develop and refine independent research skills under the supervision of more senior
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. Your key responsibilities will be to: deliver outcomes in a research project and ensure that milestones are met work with colleagues and postgraduates within the project prepare materials
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sustainable coastal development and marine management. Base Salary Level A, $113,400 - $121,054 p.a + 17% superannuation About the opportunity The School of Life and Environmental Sciences is currently seeking
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Postdoctoral Research Associate in Global Environment Modelling of Soil Organic and Inorganic Carbon
. The project is aimed to improve our in-house developed process-based computer model and use it to represent the soil ecohydrological and biogeochemical interactions across various carbon and nitrogen soil pools
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: developing and testing new approaches to water resources modelling, application of Bayesian inference methods to environmental problems, machine learning and data science applications, undertaking analysis and