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Field
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uncertainty". The goal of this project is to advance our understanding of how humans are able to act in complex and uncertain circumstances, and how such knowledge can be applied to smooth our interaction with
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other sources to train and validate AI models. Develop computational workflows incorporating LLMs, Monte Carlo Tree Search (MCTS), phylogenetic inference, uncertainty quantification, and epidemiological
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), Proficiency with LCA software tools (e.g., openLCA, SimaPro, Brightway, Activity Browser), Experience with LCA uncertainty, sensitivity analysis, and scenario modelling, Energy systems modelling and simulation
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uncertainties and result errors throughout the whole data assimilation and modeling process. ● Other Duties as assigned. Special Notes: The Research Foundation of SUNY is a private educational corporation
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uncertainties and result errors throughout the whole data assimilation and modeling process. ● Other Duties as assigned. Special Notes: The Research Foundation of SUNY is a private educational corporation
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of biological hedging shape conservation strategies? Can financial tools like biodiversity bonds or species-indexed futures promote better ecological outcomes? How should we account for uncertainty in
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learning, small data learning · Active learning, Bayesian deep learning, uncertainty quantification · Graph neural networks This position involves active participation in a well-funded
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a testbed of micromorphic numerical models, and metamaterials. Proposing experimental methods to obtain micromorphic models under small and large strain, with coupled uncertainty quantification
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a testbed of micromorphic numerical models, and metamaterials. Proposing experimental methods to obtain micromorphic models under small and large strain, with coupled uncertainty quantification
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records from satellite data, and/or improved methods of uncertainty characterisation, including the use of artificial intelligence and machine learning to improve or analyse satellite climate data records