63 Engineering-"https:" "https:" "https:" "UCL" "UCL" "UCL" Postdoctoral positions at Aarhus University in Denmark
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: http://international.au.dk/research/ The Danish School of Education The Danish School of Education at Aarhus University is Denmark’s largest centre for research and teaching in the fields of education
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Technical Sciences refers to the Ministerial Order on the Appointment of Academic Staff at Danish Universities under the Danish Ministry of Science, Technology and Innovation . The application must be in
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You have academic qualifications at PhD level within biomedical engineering, engineering, physics, medical physics, chemistry, biophysics or a related discipline. We expect applicants to have a strong
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The Department of Business Development and Technology at Aarhus University invites applications for an 18‑month postdoctoral position in AI Ethics for the Public Sector, starting 1 September 2026
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The Novo Nordisk Foundation has established a world-leading interdisciplinary research center to develop knowledge and technology for capturing and recycling carbon dioxide. The center is based
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at the Department of Electrical and Computer Engineering, Aarhus University, where we are advancing communication-efficient and distributed foundation model inference across the computing continuum
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) micro-CT imaging of breast cancer combining cutting-edge imaging technology with clinical pathology to develop quantitative 3D imaging biomarkers that bridge high-resolution micro-CT and histology. Our
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, electrical engineering, etc. Prior experience in (1) image processing, particularly for radiographic and computed tomographic data as well as mesh-type data, and (2) machine learning, particularly deep
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microscopy, optical interferometry, vacuum technology, finite element method simulations will be involved. Applicants should hold a PhD in Physics, Nano-science, Engineering or similar, experience with optics
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Join us at the Department of Electrical and Computer Engineering at Aarhus University for a postdoctoral position focused on deep learning based analysis of remote sensing data for groundwater