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-driven surrogate models for real-time reconstruction and forward simulations. Create numerical algorithms for physics reconstruction using sparse data. Implement assimilation pipelines which integrate
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to computational models. The group has a leading role in European within the fields of unconventional computing, our Comet initiative , and Computer Architecture, our CAL initiative . The position will be part of
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-economic study, design and analysis of integrated systems. Experience with energy system modeling/simulation tools (e.g., MATLAB/Simulink, Modelica, and COMSOL Multiphysics), energy systems analysis
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of future reactor systems with a focus on systems relevant for Norway. The objective is to further develop and validate machine-learning surrogate models derived from high-fidelity multiphysics simulations
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to high-performance computing facilities and datasets from laboratory experiments will be provided to support simulation and verification of the resulting model. Replicate and learn a theoretical model for
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. The objective is to further develop and validate machine-learning surrogate models derived from high-fidelity multiphysics simulations of reactor transients and quantify how surrogate uncertainties propagate
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System Model, vesion 3 (NorESM3), and a central satellite dataset for EEI is from the Clouds and the Earth’s Radiant Energy System (CERES). The specific tasks intended for the PhD fellow are to (i) Analyze
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, computationally expensive, model simulations. This experimental design process is envisioned to update iteratively as new data become available to optimally infer surface fluxes across the landscape. The work will
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approaches, generalized linear mixed modeling, and performing simulations using specialized statistical programming tools. Writing and publishing papers in international, peer-reviewed journals. An important
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modifications of the biomolecular landscape of bacterial cells contribute to bacterial physiology, pathogenesis and drug susceptibility, iii) understanding and modelling pathogenesis and treatment failure