41 cloud-computing-"https:" "https:" "https:" "https:" "https:" research jobs at Aarhus University in Denmark
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strong emphasis on publishing in leading academic journals and presenting at recognised conferences. You can read more about the Department of Management at: http://mgmt.au.dk. . Further information
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: https://ece.au.dk What we offer The Department of Electrical and Computer Engineering offers: An exciting opportunity to work on cutting-edge research in IoT systems and critical infrastructure monitoring
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collaborative relationships. Read more about the Department of Food Science at: https://food.au.dk/ The place of work is Department of Food Science, Aarhus University, Agro Food Park 48, Skejby, 8200 Aarhus N
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Join us at the Department of Electrical and Computer Engineering at Aarhus University for a postdoctoral position focused on deep learning based analysis of remote sensing data for groundwater
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personalised medicine. The Department of Biomedicine provides research-based teaching of the highest quality and is responsible for a large part of the medical degree programme. Academic staff contribute
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-field, and field-scale research facilities, advanced computing capacities as well as an extensive national and international researcher network. The department consists of nine research sections with
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, neuroscience and personalised medicine. The Department of Biomedicine provides research-based teaching of the highest quality and is responsible for a large part of the medical degree programme. Academic staff
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(including gastruloids) to study epigenetic regulation in development. An interdisciplinary environment with opportunities for collaboration across experimental and computational life sciences within MBG and
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professional laboratories, greenhouses, semi-field, and field-scale research facilities, advanced computing capacities as well as an extensive national and international researcher network. The department
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description You will be contributing to developing and implementing novel algorithms at the intersection of computational physics and machine learning for the data-driven discovery of physical models. You will