42 computing-"https:"-"https:"-"https:"-"Deutsches-Elektronen-Synchrotron-DESY" Postdoctoral positions at Aarhus University in Denmark
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The Department of Biomedicine, Faculty of Health, Aarhus University invites applications for a postdoctoral position in Computational Spatial Proteomics and Multi-Omics Integration, starting 1
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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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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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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
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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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. 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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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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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