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Aarhus BSS is now inviting applications for a number of PhD scholarships across our six academic PhD programmes. This call concerns the PhD programme in Political Science. We are looking for
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Are you passionate about mass spectrometry and are you experienced in running high resolution mass spectrometry proteomics? Department of Food Science at Aarhus University is looking for an Academic
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, the Lundbeck Foundation, Novo Nordisk Foundation, Independent Research Fund Denmark, etc. Sun lab: https://dandrite.au.dk/people/research-groups/sun-group DANDRITE: https://dandrite.au.dk
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schedule permits. About your qualifications and competence You have Completed an academic degree at the candidate or master level in a STEM discipline (e. g., Chemistry, Biology, Physics, Computer Science
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PostDoc in aerobiological modelling Are you interested in atmospheric science and can you contribute to the development of a new generation of numerical models describing concentrations and
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institutions outside the candidate's primary institution. For both positions, we expect you to have several of the following qualifications: Background in AI, bioinformatics, statistics, computer science
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Neuropeptides Employer Aarhus University (AU) Location Aarhus, Midtjylland (DK) Salary Competitive Closing date 30 Sep 2026 View more categories View less categories Discipline Life Science Job Type
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simulations on our computer cluster. The successful applicant will also contribute to disseminating the results at conferences and meetings. Your profile You must have obtained a PhD degree in physics or
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Biotech Research and Innovation Centre, The Lund Group, University of Copenhagen | Denmark | about 1 month ago
View more categories View less categories Discipline Biomedicine , Computing , Life Science Job Type Postdoctoral Employment - Hours Full time Duration Fixed term Qualification PhD Sector Academia Apply
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Bachelor’s degree in physics, computer science, computational biology, or similar fields. The applicant is expected to have demonstrated experience working with state-of-the-art deep learning approaches