154 professor-computer "https:" "https:" "https:" "https:" "https:" "Keele University" positions at Aarhus University
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Department of Management, please visit: http://mgmt.au.dk/ . Further information For further information about the position and the department, please contact Assistant Professor Gabriele Torma, email
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is a full-time permanent position. The starting date is 1 September 2026 or as agreed upon. Associate professors balance their time evenly between research and teaching activities. The successful
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The Department of Agroecology at Aarhus University, Denmark, is offering a position as Assistant professor focusing on seed science. The position will be available from 01-06-2026 or as soon as
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The Department of Clinical Medicine at Faculty of Health at Aarhus University invites applications for a position as Professor in the field of Cognitive Neuroscience as per 1 May 2026 or as soon as
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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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origami robots that can sense, compute and actuate [2]. In the recently funded RIBOTICS (RNA Origami Technology in Cell Systems) project, the lab aims to develop RNA origami robots for cell factories (yeast
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aligned to the Science Team ‘Food Quality Perception and Society’ (FQS) at the Department of Food Science http://food.au.dk/en/foodresearch/science- teams/food-quality-perception-society/. The Science Team
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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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medicine. The lab invented the RNA origami method that allows rational design of RNA scaffolds and devices for expression in cells [1] and have recently developed RNA origami robots that can sense, compute
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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