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, uncertainty propagation Where to apply Website https://imtatlantique.fillout.com/mscapf2026 Requirements Research FieldPhysicsEducation LevelPhD or equivalent Skills/Qualifications Skills: Modeling Reactor
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data, focusing in particular on the quality of Level 3 soil moisture data from the Centre Aval de Traitement des Données SMOS - Radiative transfer model in passive microwave - Uncertainty analysis
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, modeling and Remote-sensing to Transform carbon budgets, CLARiTy’ (https://www.schmidtsciences.org/vicc/) will reduce the persistently high land flux uncertainties in GCB by an order of magnitude. To achieve
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, Phnom Penh) using collected entomological time series; - Perform global sensitivity analyses (Sobol, FAST, and equivalents) to identify dominant parameters and key interactions; - Quantify uncertainty
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targets the development of advanced grey-box modeling frameworks for multiphase flow systems, combining mechanistic, multi-scale flow models with data-driven inference and uncertainty quantification
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targets the development of advanced grey-box modeling frameworks for multiphase flow systems, combining mechanistic, multi-scale flow models with data-driven inference and uncertainty quantification
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candidate in the exciting area of multiscale and multiphysics modelling of sustainable fibrous composites, with additional focus on uncertainty quantification and machine learning. Information The context
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, modeling and Remote-sensing to Transform carbon budgets, CLARiTy’ (https://www.schmidtsciences.org/vicc/) will reduce the persistently high land flux uncertainties in GCB by an order of magnitude. To achieve
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Computational Mathematics for reliable and trustworthy uncertainty quantification in science, engineering, and machine learning. Your workplace You will be employed at the Division of Applied Mathematics in a
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application! We invite applications for a fully funded PhD student position to join the research group of Jan Glaubitz to work on Bayesian Computational Mathematics for reliable and trustworthy uncertainty