202 Computer-Science-"https:"-"https:"-"https:"-"https:"-"https:"-"https:" "https:" positions in Denmark
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students. We therefore seek candidates with an open, constructive, and collaborative approach The Department of Biology The Department of Biology (http://bio.au.dk/ ) provides a framework for research and
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At the Faculty of Engineering and Science, Department of the Built Environment (BUILD), a 3-year position as Assistant Professor in Urban and Regional Science is open for appointment in the Division
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electronic components by integrating thermal design directly into the early stages of technology and component development, this position may be the right opportunity for you. We are looking for an Assistant
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and 95 PhD students. The department is responsible for two educations: Molecular Biology and Molecular Medicine with a yearly uptake of 160 students in total. Please refer to http://mbg.au.dk
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employees with Greenland as our primary base for Arctic science activities, and we are strongly anchored in the Greenland Ecosystem Monitoring (GEM) programme and to research and advise related to industrial
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department can be found at: http://www.ind.ku.dk/ . Job description We are looking for a distinguished scholar in science engagement research to join a growing research group in the department that focuses
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The Department of Political Science at Aarhus BSS, Aarhus University, is seeking ambitious and dedicated scholars to join one of Europe’s leading political science environments, offering excellent
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of Civil and Architectural Engineering Theme 9: Building the resilient, flexible, multi-energy microgrids of tomorrow hosted by the Department of Electrical and Computer Engineering Theme 10: Advanced
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15 Jul 2026 Job Information Organisation/Company Aalborg Universitet Department The Faculty of Medicine, Deanship, SUND, Deans Office, Health Research Field Medical sciences » Medicine Researcher
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, computer science, computational biology, or similar fields. The applicant is expected to have demonstrated experience working with state-of-the-art deep learning approaches for detection and/or classification