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reNEW, a part of the Department of Biomedical Sciences at the University of Copenhagen, is looking for an academic employee to join the Żylicz group starting April 1, 2026 or upon agreement with
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PhD Project in Laser Enhanced Fabrication of Quantum Devices Niels Bohr Institute Faculty of SCIENCE University of Copenhagen The Novo Nordisk Foundation Quantum Computing Programme (NQCP) is
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The Department of Economics, Faculty of Social Sciences, University of Copenhagen (UCPH) invites excellent candidates for a part-time associate professorship. The position is a permanent, part-time
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key agroecosystem variables. These variables include cover crop growth, crop nitrogen, yield, and tillage practices. You will develop novel algorithms to integrate data-driven machine learning and
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key agroecosystem variables. These variables include cover crop growth, crop nitrogen, yield, and tillage practices. You will develop novel algorithms to integrate data-driven machine learning and
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molecular docking and virtual screening. Similar facility manager roles in the past. Place of employment The place of employment is at the Department of Drug Design and Pharmacology, University of Copenhagen
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12 Nov 2025 Job Information Organisation/Company University of Copenhagen Department Novo Nordisk Foundation Center for Basic Metabolic Research (CBMR) Research Field Computer science Biological
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. Experience with machine learning techniques for neural data analysis. Track record of publications in high-impact journals and successful grant applications. Work Environment: This position is part of a
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landscape analyses with backgrounds in biogeochemistry, agronomy, biology, geography, and social sciences from Aarhus University and University of Copenhagen, as well as our international partners: Colorado
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Bioinformatics Staff Scientist at the Center for Adipocyte Signaling (ADIPOSIGN) (Academic Employee)
for exploratory data analysis and data sharing Experience in Machine Learning would be desirable Passion for complex data visualization and representing data into interpretable figures. Ideally at least one major