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for understanding their reliability and for making informed decisions based on their predictions. This project aims to develop new methods for uncertainty quantification in mathematical and statistical models
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-models, thereby avoiding double counting of effects, • developing and evaluating temporal machine-learning models for sequence-to-sequence prediction of fuel behaviour, • extending surrogate models
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working conditions? We welcome you to apply for a PhD position at the Department of Information Technology, Uppsala University. The Department of Information Technology holds a leading position in both
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research in data-driven nutrition, health, and food science. With large-scale diet and health data, omics data, biomarkers, digital food and health services, we establish predictive models for evaluation
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prediction, most current models still describe proteins largely as static structures and do not fully capture the conformational ensembles that underlie protein function. This PhD project aims to address
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. At the Division of Systems and Control , we develop both theory and concrete tools to design systems that learn, reason, and act in the real world based on a seamless combination of data, mathematical models, and