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-driven life science framework. 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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to receiving your application! 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
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studies. About the DDLS program Data-driven life science (DDLS) combines data, computational methods, and artificial intelligence to study biological systems from molecular structures to human health and
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The Department of Cell and Molecular Biology (ICM) (https://icm.uu.se) is organized into seven research programs, each focusing on distinct areas within cell and molecular biology i.e. computational
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together with their supervisors, as well as with other doctoral students and postdocs in the supervisors’ groups. Data-driven life science (DDLS) uses data, computational methods and artificial intelligence
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-supervisors, as well as with other doctoral students and postdocs in the supervisors’ lab. Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological
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discovery by integrating artificial intelligence with synthetic biology to target “undruggable” proteins. The project is a collaboration between the national SciLifeLab Drug Discovery & Development platform
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epidemiology and biology of infection, which is a fully funded, four-year PhD student position. Data-driven life science Research School Data-driven life science (DDLS) uses data, computational methods, and
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of the SciLifeLab Integrated structural biology platform https://www.scilifelab.se/units/structural-proteomics/ The unit provides access to cutting-edge equipment and expertise, for the analysis
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(Stockholm, Sweden) and the candidate will benefit from a strong (inter-)national network of collaborators in protease biology and computational proteomics. The successful candidate for this position will join