46 embedded-system "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" "UCL" "UCL" positions at Linköping University in Sweden
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apply innovative methods for environmental research, often in collaboration with other universities or non-academic organizations. The VERIFARM project, funded by Formas, is an interdisciplinary research
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of machine learning which clearly integrates the two subject areas within the division. For more information about STIMA, please see https://liu.se/organisation/liu/ida/stima . Linköping University is
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priority research areas. Since 2008 REMESO’s PhD education is integrated with an international Graduate School in Migration, Ethnicity and Society. More about the REMESO research environment here https
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distributed wireless systems" which is conducted in collaboration between Linköping University (LiU) and Lund University (LU). Read more here: https://elliit.se/project/machine-learning-for-sensing-in
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application! We are looking for a PhD student in Medical Science Your work assignments Viral gastroenteritis, mainly caused by norovirus and rotaviruses, is a leading cause of global diarrhea. Susceptibility
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research grants by the senior faculty members. Read more about our activities at https://liu.se/en/research/cybersecurity and https://www.rics.se/ . The employment This employment is a temporary contract of
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of Sweden and is part of the EU’s ambitious AI Factories initiative. Learn more: https://mimer-ai.eu/about-mimer/ , https://www.naiss.se , https://eurohpc-ju.europa.eu/ai-factories_en We are now looking for
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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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stimulating environment and to contribute to a deeper understanding of the foundations of optimization and their role in modern applications. The position is funded by WASP (Wallenberg AI, Autonomous Systems
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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