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parametric reduced order models of operating wind turbines, information contained in their differential geometry and safe data-driven control/reinforcement learning tools jointly developed with the second PhD
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issues. It is therefore essential to be able to predict and control the moisture state in construction materials. Traditional material characterization methods, standards and models for hygrothermal
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, large-scale foundation models will be developed and trained on the Aalborg Supercomputer (TAAURUS), facilitating advanced ECG representation learning and prediction of acute coronary events in
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design and laboratory experimentation, you will first explore a broad range of sodium-oxide glass compositions using advanced computer models to predict how well ions can move through them. Based