12 application-forms "https:" "https:" "https:" "IFM" "IFM" "IFM" "IFM" Postdoctoral positions at Linköping University
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. Information about the workplace: https://liu.se/en/organisation/liu/ifm https://liu.se/en/research/m2lab The employment This employment is a temporary contract of two years with the possibility of extension up
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7 Feb 2026 Job Information Organisation/Company Linköping University Research Field Biological sciences Researcher Profile Established Researcher (R3) Application Deadline 31 Mar 2026 - 12:00 (UTC
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participation in regular group meetings and events. You can read about the workplace: https://liu.se/en/organisation/liu/ifm/mdesign The employment This employment is a temporary contract of two years with
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application! Work assignments AIR2 is a five-year multidisciplinary national project financed by the Wallenberg AI, Autonomous systems, and Software Program (WASP) whereby you will have the opportunity
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application! Work assignments The postdoc project will investigate how children of different age groups perceive and experience different types of interactive artificial intelligence (AI), such as chatbots and
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application! The workplace You can read about the workplace at Division of Applied Mathematics, WASP at Department of Mathematics and Work at MAI . Work assignments As a postdoctoral researcher, you will
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application! Work assignments The multi-disciplinary centre for cyber resilient AI, RESIST, is a national effort funded by the Swedish Strategic Research Foundation (SSF) to bring together leading researchers
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application! Work assignments The postdoctoral fellow will work within ASC’s research field ‘ageing and work‘ in close collaboration with the Swedish Research Centre for Return to Work in Later Life RELATE
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technologies. The OEM group is part of the Laboratory of Organic Electronics (LOE) (https://liu.se/LOE ), an internationally renowned research environment comprising more than 150 researchers from diverse
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application! Work assignments This position focuses on the development of theoretically grounded and practically scalable decentralized learning algorithms under realistic system constraints, including