14 modelling-complexity-geocomputation Postdoctoral positions at University of Sydney in Australia
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Postdoctoral Research Associate in Global Environment Modelling of Soil Organic and Inorganic Carbon
- $121,054 + 17% superannuation About the opportunity The School of Civil Engineering at The University of Sydney is recruiting for a Postdoctoral Research Associate in Global Environment Modelling of Soil
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Full time, 3-year fixed term, located on the Camperdown Campus at the Faculty of Science Join a cutting-edge ARC Linkage project advancing fish seascape ecology and connectivity modelling to inform
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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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) Demonstrated research expertise in one or more of the following: AI/ML algorithm development (e.g., PyTorch, TensorFlow, scikit-learn) dynamic modelling and simulation of complex systems reinforcement learning
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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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the first of its kind. EarthBank functionalities are continuing to expand beyond its current range of data types, which includes relational data models for major, minor and trace element geochemistry, U-Th-Pb
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ARC DP project aiming to develop of hybrid asymptotic methods based on exponential asymptotics and computational complex analysis apply these methods to applied nonlinear problems arising from water
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cancer therapies, including gene- and cell-based immunotherapies. You will work with state-of-the-art technologies such as single-cell multiomics, stem cell models, and nanotechnology, within a
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related field experience in the development of machine learning models using Python and pytorch expertise in two or more of the following technical areas: design of FPGA-based accelerators, high-level
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, Psychology, or a related field. strong background in computational modelling and/or functional neuroimaging techniques. proficiency in programming languages commonly used in neuroscience research (e.g., Python