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of Information Technology website . The position is hosted by the Division of Scientific Computing (TDB) within the Department of Information Technology. As one of the world’s largest focused research environments in
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Assistant professor in Computational biology -machine learning for multimodal molecular biology data
direct connection with NGI Stockholm. Subject field Computational biology with a focus on machine learning for multimodal molecular biology data. Subject description The subject covers the development and
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direct connection with NGI Stockholm . Subject field Computational biology with a focus on machine learning for multimodal molecular biology data. Subject description The subject covers the development and
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sciences. For example, high-performance computing makes it possible to design more efficient wind turbine blades and wind farms, to predict the structure of proteins, to understand how the COVID virus
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One Ph.D. position is available in stochastic modelling of infectious diseases. The research project is focused on healthcare-acquired infections with the long-term goal of developing computational
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that change? Then join us in this unique program! About the position Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all
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that change? Then join us in this unique program! About the position Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all
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at http://ki.se/en/meb This PhD program is part of the SciLifeLab and Wallenberg National Program for Data-Driven Life Science (DDLS). Data driven life science Data-driven life science (DDLS) uses data
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information can be found at http://ki.se/en/meb This PhD program is part of the SciLifeLab and Wallenberg National Program for Data-Driven Life Science (DDLS). Data driven life science Data-driven life science
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to develop computational algorithms and methods that use omics data to infer gene regulatory networks (GRNs), and apply these to understand regulatory mechanisms that lead to cancer formation. Cancer