57 engineering-computation "https:" "https:" "https:" "https:" "UNIV" positions at Linköping University in Sweden
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conduct research on the theoretical foundations of mathematical optimization, as well as its applications to emerging challenges in machine learning and engineering. You will write and submit research
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for candidates with a Ph.D. in Electrical Engineering or equivalent, a strong mathematical background and a strong publication record in journals relevant to the research field. As the university operates in
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advances research on the changing material conditions of media, technology, culture and heritage, and how they intersect with environmental, institutional, industrial, and social conditions. Research in
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17 Mar 2026 Job Information Organisation/Company Linköping University Research Field Computer science Researcher Profile First Stage Researcher (R1) Application Deadline 13 Apr 2026 - 12:00 (UTC
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electrophysiology and fluorescence-based techniques, and screening of potential modulatory compounds. The project involves collaborations with computational research groups and integrates both manual and automated
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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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conducted in collaboration between Linköping University (LiU) and Lund University (LU). Read more here: https://elliit.se/project/machine-learning-for-sensing-in-distributed-wireless-systems/ Distributed MIMO
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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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/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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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