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phasing in humans and other species. In this project, we aim to develop machine learning models to advance the characterization of genetic variations. Research project 3. De novo genes are genes that arise
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organization – and how these changes intersect with immunosuppressive mechanisms that allow tumors to evade immune surveillance. By integrating advanced biophysical characterization techniques with functional
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candidate will join the Scientific Machine Learning group at TDB and SciLifeLab. The group develops theory, methods and software for data-driven science, with a current focus on uncertainty quantification
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documents (translated into Swedish or English), A list of publications, Up to five selected publications in electronic format A research statement describing your past and current research (max 1 page) and a
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positions, academic title, current position, academic distinctions, and committee work A complete list of publications A summary of current work (no more than one page) The application is to be submitted