12 algorithm-development-"LIST" Postdoctoral positions at University of Sydney in Australia
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understanding of non-stationary complex systems through theoretical analysis and numerical simulation develop efficient statistical algorithms for analyzing and inferring dynamical models from multivariate time
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, Medicine, or Engineering) demonstrated experience or knowledge of one or more of the following: computational algorithm development working with medical images, in particular CT or cone-beam CT a
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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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will apply and develop expertise in conducting research to further the research agenda of the Lab, School and Faculty. The successful applicant will contribute to research efforts independently asand
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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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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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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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: 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