62 engineering-computation "https:" "https:" "https:" "https:" "https:" "https:" "U.S" "U.S" Postdoctoral positions at Aarhus University in Denmark
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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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://international.au.dk/research/ Aarhus University 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
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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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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 obtained from Head of Research Unit Peter
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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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in the areas listed here: https://math.au.dk/en/about/vacancies/postdoc/ When applying, you will be asked to indicate, which of the areas listed on the page above are of interest to you. The list
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Science in Engineering, and around 800 students are enrolled in our study programs. Furthermore, we also offer an ambitious PhD program. At the Department of Biological and Chemical Engineering, focus is on
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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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We invite applications from researchers to join our XR (extended reality) and Visual Computing research groups. We have 3 posts available from 1 May but there is flexibility for later start dates
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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