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of Infrastructures at the Department of Life Sciences, Chalmers University of Technology. CMSI provides advanced mass spectrometry-based analytical services and expertise, with a particular focus on metabolomics and
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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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Uppsala University, Disciplinary Domain of Science and Technology, Faculty of Mathematics and Computer Science, Department of Information Technology Are you interested in working with probabilistic
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-based approaches often lack principled uncertainty quantification, limiting their reliability in healthcare applications. This project aims to develop mathematically grounded methods based on probability