73 parallel-computing-"https:" Postdoctoral research jobs at Aarhus University in Denmark
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about the faculty here . About the research project We are seeking a highly motivated postdoctoral researcher to join the QuantuMRI programme, funded by the Novo Nordisk Foundation’s Interdisciplinary
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recommendation by CNN (https://edition.cnn.com/travel/article/aarhus-denmark-things-to-do/index.html ). Aarhus is easily reached via local international airports in Jutland within 1 hour of Aarhus, or via
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. Your competences You have academic qualifications at PhD level. Candidates can have a background in a (bio)medical discipline (incl. medicine or dentistry), medical physics, computer/data science
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₂ Research Center (CORC). The successful candidate will contribute to the HyperCap research program by developing improved and cost-efficient synthesis routes for thermodynamic promoter systems used in gas
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. For further information about the school, please see http://cas.au.dk/en/ . For more information on the Locally Crafted Empires project, please see https://projects.au.dk/locally-crafted-empires
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research profile within organisational studies, Computer-Supported Cooperative Work, Human-Computer Interaction or related research areas as documented by a PhD dissertation and/or research publications
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Development Programme targeted at career development for postdocs at AU. You can read more about it here . The application must be submitted via Aarhus University’s recruitment system, which can be accessed
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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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environment that supports this equilibrium. You can read more about family and work-life balance in Denmark . Aarhus University also offers a Junior Researcher Development Programme targeted at career
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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