428 systems-science "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" uni jobs in Sweden
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28 Mar 2026 Job Information Organisation/Company Chalmers University of Technology Research Field Computer science » Other Economics » Environmental economics Engineering » Other Environmental
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biochemistry, medicinal chemistry and structural biology to understand structure and function of biological macromolecules and to manipulate their function, e.g. by drug development. More information at https
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NAISS, the National Academic Infrastructure for Supercomputing in Sweden, provides academic users with high-performance computing resources, storage capacity, and data services. NAISS is hosted by
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28 Mar 2026 Job Information Organisation/Company Chalmers University of Technology Research Field Astronomy » Astrophysics Astronomy » Other Economics » Administrative sciences Economics
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to identifying and evaluating different pathways toward sustainable energy systems. About us At the Division of Energy Technology , we develop and analyse sustainable energy systems and conversion technologies
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Medical Science Project title: RNA-modifications and Cancer biology The Department of Laboratory Medicine is located at the Institute of Biomedicine at the Faculty of Medicine at Sahlgrenska Academy
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presentations. About us The Department of Aquatic Sciences and Assessment is working with applied environmental science, with a national responsibility for assessing the condition of Swedish surface waters with
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28 Mar 2026 Job Information Organisation/Company Chalmers University of Technology Research Field Astronomy » Astrophysics Astronomy » Other Chemistry » Other Physics » Quantum mechanics Physics
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/InstituteSchool of Electrical Engineering ans Computer ScienceCountrySwedenState/ProvinceStockholmCityStockholmPostal Code10044StreetBrinellvägen 8Geofield Contact City Stockholm Website https://www.kth.se/en
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recruiting 1-2 doctoral students on technology foresight for policy-driven low-carbon technologies. One position will focus on technology foresight developing data-driven approaches for probabilistic modelling