66 structural-engineering "https:" "https:" "https:" "UCL" "UCL" positions at SciLifeLab in Sweden
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Qualifications You must have at least 240 higher education credits (hc), of which at least 60 hc are at an advanced level, in natural sciences, life sciences, or engineering Applicants must be skilled in both oral
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Engineering” (TPE) is attached to KTH and located at SciLifeLab DDD, Solna. The unit’s main responsibility is to deliver well-characterized antibodies, antigens, and target proteins to the projects, as
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at the Division of Biomedical Engineering Department of Materials Science and Engineering, Uppsala University. Full-time temporary position for two years starting as soon as possible or as agreed
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future. 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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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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for therapy. To do this, we interrogate the spatial relationships between B and T cell clones and their immediate niches within tissues using our in-house developed spatial transcriptomics-based technology
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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 processes
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of Science and Technology and conducts research in biochemistry, organic chemistry, analytical chemistry, and physical chemistry. The research is focused on catalysis, molecular recognition, structure and
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: https://www.slu.se/institutioner/vaxtbiologi-skogsgenetik/ Read more about our benefits and what it is like to work at SLU: https://www.slu.se/om-slu/jobba-pa-slu/ PhD Student: DDLS integrative
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School of Engineering Sciences in Chemistry, Biotechnology and Health at KTH Project description Third-cycle subject: Biotechnology The project aims to develop probabilistic deep learning models