79 assistant-professor-computer-science-data "https:" "https:" "https:" "https:" "Dr" "St" "St" Postdoctoral positions at Aarhus University in Denmark
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19 Mar 2026 Job Information Organisation/Company Aarhus University Department Department of Molecular Biology and Genetics Research Field Biological sciences » Biological engineering Researcher
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The Section for Electrical Energy Technology at the Department of Electrical and Computer Engineering (ECE), Aarhus University, is in a phase of rapid growth in both education and research
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. Qualifications Applicants must hold a PhD or equivalent qualifications in a relevant field, such as Child–Computer Interaction, Human–Computer Interaction, Learning Sciences, Educational Technology, Computer Science
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(2014). https://doi.org/10.1126/science.1253920 [2] An RNA origami robot that traps and releases a fluorescent aptamer. Science Advances (2024). https://doi.org/10.1126/sciadv.adk1250 Your qualifications
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permanent staff of 43 full, associate and assistant professors, a support staff of ~40 technical and administrative staff, ~150 PhD-students and ~100 postdocs and around 350 students. In
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collaboration. Please refer to Department of Animal and Veterinary Sciences (au.dk) for further information about the department; https://anivet.au.dk/en Contact Further information on the position may be
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science. Preferably you have a background in STM/STS, photoelectron spectroscopy (ARPES, XPS) or Atomic Force Microscopy (AFM). Preferably you have experience with Ultra High Vacuum sample preparation
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. Applicants seeking further information are invited to contact Associate Professor Florin Musat (florin.musat@bio.au.dk) . Who we are The successful candidate will be employed by the Department of Biology at
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The Department of Ecoscience at Aarhus University invites applications for two postdoctoral positions to strengthen our research on image recognition, computer vision and deep learning applied
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University. Dr Speed's research involves developing statistical methods for better analysing data from genome-wide association studies (GWAS), with a particular focus on improving our understanding of human