188 computational-physics "https:" "https:" "https:" "Mines Paris PSL" scholarships in Sweden
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physics, electrical engineering, image processing, computer vision, AI, machine learning, data science, computer science, applied mathematics, or in a similar field, or have completed at least 240 credits
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Job related to staff position within a Research Infrastructure? No Offer Description The Department of Physics at Umeå University (https://www.umu.se/en/department-of-physics/ ) conducts strong research
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=sv The employment When taking up the post, you will be admitted to the program for doctoral studies. More information about the doctoral studies at each faculty is available at https://liu.se/en
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education to enable regions to expand quickly and sustainably. In fact, the future is made here. The Department of Physics at Umeå University (https://www.umu.se/en/department-of-physics/ ) conducts strong
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Stage Researcher (R1) Application Deadline 30 Apr 2026 - 21:59 (UTC) Country Sweden Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not
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3 Mar 2026 Job Information Organisation/Company Umea University Research Field Physics » Biophysics Chemistry » Physical chemistry Engineering » Biomedical engineering Researcher Profile First Stage
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biology, physics, applied mathematics, computer science, bioinformatics, structural biology, or a related subject or completed courses with a minimum of 240 credits, at least 60 of which must be in advanced
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level in computational biology, physics, applied mathematics, computer science, bioinformatics, structural biology, or a related subject or completed courses with a minimum of 240 credits, at least 60 of
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physical geography, for research on the role of perennial snowfields in the water cycle in northern Sweden, with special focus on evapotranspiration. The start date is fairly flexible but ideally sometime
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the Arctic, experimental tests of climate driven changes in carbon export from land and turnover and release of greenhouse gases (CO2 and CH4 ) from headwaters, and use of machine learning and process-based