59 data "https:" "https:" "https:" "https:" "Dr" "L2CM" positions at Linköping University
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scientific literature in the field, contribute to experimental planning, and critically assess experimental data. The following education, experience and expertise are required: A Master’s degree in biology
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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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/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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. More information about the research environment and workplace can be found here: https://liu.se/en/research/laboratory-of-organic-electronics/organic-energy-materials The employment This post is a
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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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of Computer and Information Science , within Linköping University . Your work assignments As a PhD student, you devote most of your time to doctoral studies and the research projects of which you are part. Your
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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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competitive advantage (https://liu.se/en/research/cbmi ). You will work under the supervision of Professors Christian Kowalkowski and Daniel Kindström. Research at IEI spans a broad range of areas, from
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of existing bioinformatic workflows and development of new pipelines. The analyses will be carried out on GPUs and part will consist of data processing and visualization in order to facilitate interpretation
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methods to provide explainable outputs from AI models in presence of attacks on the models or data, and scalable methods that move beyond feature attribution aiming for root cause analysis and decision