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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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modelling and simulation of complex systems reinforcement learning or graph neural networks proficiency in Python and related computational toolchains a strong interest in interdisciplinary research bridging
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Computer Engineering at the University of Sydney is seeking to appoint a Research Associate or Postdoctoral Research Associate to contribute to an exciting project focused on the challenge of accelerating
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-scale, complex project environments. This project is part of an ambitious research program to integrate real-time sensing, AI-based control, and governance analytics into the future of infrastructure and
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applications of data science and modelling. The successful candidate will support the research of Professor Lucy Marshall, Faculty of Engineering and will collaborate with members of her cross-institutional
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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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27 Aug 2025 Job Information Organisation/Company UNIVERSITY OF SYDNEY Research Field Computer science Researcher Profile Recognised Researcher (R2) Established Researcher (R3) Country Australia
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neuroimaging (particularly functional) is required, and ideally the candidate will have experience in linking imaging methods with cognitive, neurobiological or computational modelling frameworks. Your key
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in the Tumour Inflammation and Immunotherapy Program at SAiGENCI combine molecular biological and genetic approaches, together with human translational studies, to identify the mechanisms by which
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sedimentology, paleoecology, paleoclimatology, numerical modelling, relational database design, and geological data science a strong track record of publications in leading international scientific journals (Q1