19 learning-"https:" "https:" "https:" "https:" "https:" "https:" "University of Copenhagen" positions in Denmark
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, Section for Copenhagen, Natural Language Processing The Department of Computer Science at The Technical Faculty of IT and Design invites applications for two or more postdoc positions in the area of
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Biotech Research and Innovation Centre, The Lund Group, University of Copenhagen | Denmark | about 2 months ago
, University of Copenhagen Employer Biotech Research and Innovation Centre, The Lund Group, University of Copenhagen Location Copenhagen, Hovedstaden (DK) Salary Competitive Closing date 13 Sep 2026
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project. Aalborg University applies a problem-based learning (PBL) approach. Documented experience with PBL (such as project supervision, facilitation of group processes, and development of PBL-based
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Ice Sheet Employer GEUS Location Copenhagen, Hovedstaden (DK) Salary Salary and terms of employment are in accordance with the relevant trade union agreement. Closing date 1 Nov 2026 View more
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-time data into WRF-Chem • You will be contributing to the development of machine learning models used on data from Poleno Jupiters, applying Python and machine learning. • The position will focus
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in Odense Employer University of Southern Denmark (SDU) Location Odense, Fyn (DK) Salary Competitive Closing date 15 Nov 2026 View more categories View less categories Discipline Chemistry , Health
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evaluated. The application deadline is 27 September 2026 at 11.59 PM/23.59 (CET/CEST) The University of Southern Denmark wishes to reflect the surrounding community and therefore encourages everyone
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The National Institute of Public Health at the University of Southern Denmark (SDU) invites applicants for a 3-year PhD scholarship for a highly motivated candidate interested in working within the
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poisonous books conducted in collaboration with the Royal Academy in Copenhagen, Pisa University, and the Library at SDU ( https://www.nature.com/articles/s40494-019-0334-2 ). About the candidate The
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agricultural areas in Denmark You will be contributing to the dynamical integration of near real-time data into WRF-Chem You will be contributing to the development of machine learning models used on data