49 engineering-computation-"https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" positions at Linköping University
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Social Robots, which involves several Swedish universities and is funded by WASP-HS (https://wasp-hs.org/ ). The Wallenberg AI, Autonomous Systems and Software Program – Humanity and Society (WASP-HS) is a
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/tensions between the global North and global South. We will also consider applicants focused primarily on Swedish/Nordic cases or topics. For full information of the five REMESO research streams see: https
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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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most two pages, explaining your motivation, research goals and why you fit the advertised position. The workplace The Department of Computer and Information Science was founded in 1983, but its roots go
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application! We are looking for a PhD student in Statistics and Machine Learning Your work assignments We are looking for a PhD candidate to work in the intersection of computational statistics and machine
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workplace The Division of Industrial Management at the Department of Management and Engineering (IEI) conducts research and provides undergraduate, postgraduate, and doctoral education in marketing and
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induction. You will combine advanced genetic engineering approaches with survival assays, fluorescence-based techniques in fixed and live cells, single-cell sequencing, and computational bioinformatics
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communication, user-oriented, and always curious about better solutions for the best user experience. The workplace You will belong to the Department of Technology and Natural Sciences, but work closely with
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Management Lab (KDMLAB) of the Department of Computer and Information Science at Linköping University. The department is one of the largest computer science departments in northern Europe, with research
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, and datasets; often at substantial computational and environmental costs. This PhD project targets sustainable and resource-efficient machine learning with a focus on methods that reduce compute, energy