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methods based on optimal transport for addressing problems in signal processing, control theory, and inverse problems. The doctoral student project and the duties of the doctoral student By developing novel
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. The data-driven life science initiative Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular
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on biological processes as well as the impact of biological processes on materials. Our ambition is to foster a dynamic teaching and research environment that is internationally recognized for its excellence in
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to benefit from studies at the doctoral level. After the selection of the suitable candidate, the process for the admission to doctoral studies will commence. An admission decision will be taken by
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, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular processes to human health and global ecosystems. The SciLifeLab
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variability in risk factor susceptibility, treatment response, disease pathogenesis, and clinical diagnosis (biostatistics, machine/deep learning), ii) Investigating causal processes and disease mechanisms