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the Royal Institute of Technology, Stockholm. Dahlin’s team works at the intersection between experimental and computational medicine to map blood cell development at the single-cell level. This is performed
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university. More information about us, please visit: the Department of Biochemistry and Biophysics . Project description Project title: Biology-informed Robust AI Methods for Inferring Complex Gene Regulatory
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Complex Systems and Biophysics and is performed in an international environment with extensive national and international collaborations. The education programs at the Department include Bachelor- and
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identify systems-level mechanisms in cancer that can be used to uncover new biomarkers, drug targets, and paths to drug resistance. The long-term goal of our lab is to enable computer-aided design of
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Uppsala and in Sweden at large. For information about the SciLifeLab fellow program, see https://www.scilifelab.se/research/#fellows. SciLifeLab Fellows are also part of a broad national network of future
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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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. The ongoing societal transformation and large green investments in northern Sweden create enormous opportunities and complex challenges. For Umeå University, conducting research about – and in the middle of – a
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) strategies, primarily revolving around interpretable ML and generative AI, to study complex biological processes. This project combines timely analytical challenges with deep rooted applications in life
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to alter and characterize the 3D cell cultures including their microenvironment. For evaluation you will use a combination of computational and experimental techniques, including e.g. numerical modelling
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at the Wallenberg Laboratory. The group is part of the national Data-Driven Life Science (DDLS) program, funded by the Knut and Alice Wallenberg Foundation. Their research focuses on developing computational methods