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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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patients develop a durable response. Many researchers are investing efforts to understand the complexity of anti-cancer immunity and develop diagnostic approaches that accurately predict therapy benefit and
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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