143 computational-physics "https:" "https:" "https:" "https:" "INRAE" positions at Aarhus University
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collaboration with industry? The Department of Electrical and Computer Engineering at Aarhus University is looking for a R&D Engineer (TAP) position from April 15, 2026 or as soon as possible. This is a fixed
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for ensuring biosecurity for animals kept outdoors Development and evaluation of a training and testing programme targeting European pig inspectors to monitor tail lesions at slaughter The preferred candidate
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work. Qualifications PhD in computer science, computational biology, engineering, or related fields. Experience developing deep-learning tools for image processing, automatic monitoring of agricultural
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. Together with your co-mentor, you will have the opportunity to shape and develop the mentor programme so it aligns with your strengths and the needs of your group. Your work will be supported by the BCE
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interdisciplinary center for research and education in quantitative genetics and quantitative genomics (http://www.qgg.au.dk/en). QGG is an international organization with 70 employees and visiting researchers from
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”, affiliated with the Danish Innovation Index (DII) at the PhD Programme Management, and will establish the Danish Innovation Index as a research excellence group at the Department. The positions are available
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Society at the Department of Food Science, Aarhus University ( http://food.au.dk/en/foodresearch/science-teams/food-quality-perception-society/ ). The position will be affiliated to science-based advice
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good industrial and professional 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
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also offers a Junior Researcher Development Programme targeted at career development for postdocs at AU. You can read more about it here: http://talent.au.dk/junior-researcher-development-programme
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hold a PhD in oceanography, marine ecology, computer sciences, data sciences or similar. We expect that you have: Expert knowledge on network modelling, especially aimed at ecological applications Strong