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. Project description Data-driven mathematical and statistical models are increasingly used in life science research and healthcare. Quantifying the uncertainty associated with these models is crucial
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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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methodological perspective and from the perspective of data-driven science applications. It is an arena where experts in computational science, data science and data engineering (systems and methodology) work
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and variation. The successful candidate will develop innovative methods and models to advance our understanding of genome evolution and variation. The position is based in the Computational Genomics
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expertise. Are scientifically curious, independently driven, and motivated by biologically meaningful modelling problems. Have good teaching abilities. Have awareness of diversity and equal opportunity issues
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Royal Institute of Technology, Stockholm University and Uppsala University. The center also collaborates with several other universities. The employment will be placed at the Department of biochemistry
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to develop and utilize innovative, interpretable data-driven analysis methods to significantly advance our understanding of immune cell inter-relations within the cancer microenvironment. We will apply
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Institutet, KTH Royal Institute of Technology, Stockholm University and Uppsala University. The center also collaborates with several other universities. The employment will be placed at the Department
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Are you interested in developing mathematically grounded methods for uncertainty quantification in deep learning, particularly for large language models in healthcare applications? Are you looking
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at the Division of Biomedical Engineering Department of Materials Science and Engineering, Uppsala University Full-time temporary position for two years starting in September 2026, or as agreed upon