15 parallel-and-distributed-computing "Multiple" PhD positions at Linköping University in Sweden
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30 Aug 2025 Job Information Organisation/Company Linköping University Research Field Computer science » Digital systems Technology » Information technology Technology » Interface technology
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facilitate data sharing among actors involved in a new circular flow of flat glass. Within the project, two PhD students, one at the Department of Computer and Information Science (with computer
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Sweden Application Deadline 23 Sep 2025 - 22:00 (UTC) Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Reference
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. Official transcripts from BSc and MSc degrees, including information on which courses you have taken. 1-2 writing samples. These can be theses work, publications etc. If there are multiple authors on a
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application! We are looking for up to two PhD students in trustworthy machine learning, with a particular focus on cybersecurity, privacy, and verifiability for AI systems, based at the Department of Computer
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treatment. It is advantageous if you have previously worked with massively parallel sequencing (NGS), both in the laboratory and/or with bioinformatics, for example Single Cell RNAseq. It is also advantageous
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, localization, and sensing, with a focus on developing next-generation multiple-antenna systems while optimizing overall system performance. As a doctoral student, you devote most of your time to doctoral studies
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part of the national research program WASP. Wallenberg AI, Autonomous Systems and Software Program (WASP) is Sweden’s largest individual research program ever, a major national initiative for
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30 Aug 2025 Job Information Organisation/Company Linköping University Research Field Computer science » Other Researcher Profile First Stage Researcher (R1) Country Sweden Application Deadline 29
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cross-disciplinary research initiative involving both computer and material scientists, providing excellent opportunities for practical impact by taking the outputs from the developed machine learning