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strategy and organizational structure of the program in close collaboration with the Scientific Directors Prof. Jan Ellenberg and Prof. Mathias Uhlén. Coordinate and monitor research activities, recruitments
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new flagship research program aiming to to map the molecular structure and function of single human cells in time and space and create AI-based models to predict human cells. It is funded by the Knut
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year project, funded by the DDLS program, we aim to develop AI-based tools in design of affinity ligands, such as the prediction of binding interactions between proteins. Data-driven life science (DDLS
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) program. Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular
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to study host-microbiome interactions at the spatial level in the colon. The research activities of the doctoral student will focus on the experimental and computational analysis of spatial gene expression
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have a background in bioinformatics, computational cancer biology, or related fields with experience in cancer and data-driven research. For more details about our research visit: www.alundberg.org
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. The candidate will combine experimental and computational approaches. The project will start with bioinformatics-driven analysis, followed by integration of data generated from experimental models. Over time, the
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life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular processes to human health
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. The research group is part of the National Program for Data-driven Life Science (DDLS), generously funded by the Knut and Alice Wallenberg Foundation: www.scilifelab.se/data-driven/ Our group focuses on studying
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. David Marlevi, Prof. Ulf Hedin, and Dr. Ljubica Matic to improve stroke risk prediction for patients with carotid atherosclerosis using a multidisciplinary combination of data-driven imaging