658 computer-"https:"-"APOS-UFFICIO-CONCORSI-DOCENTI" "https:" "https:" "https:" positions in Sweden
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18 Jan 2026 Job Information Organisation/Company Umeå universitet Department Umeå University, Faculty of Science and Technology Research Field Computer science Researcher Profile First Stage
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Deadline 19 Mar 2026 - 22:59 (UTC) Country Sweden Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job
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) Application Deadline 6 Mar 2026 - 22:59 (UTC) Country Sweden Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the
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equivalent knowledge acquired in other ways, in Sweden or abroad. Assessment grounds The assessment will focus on the applicant's ability to successfully complete the doctoral program. Particular emphasis is
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complete the doctoral program. Particular emphasis is placed on the candidate’s motivation, ability to conduct doctoral studies, as well as the breadth and composition of previous education. It is of benefit
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(UTC) Country Sweden Type of Contract To be defined Job Status Full-time Hours Per Week To be defined Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the
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24 Jan 2026 Job Information Organisation/Company KTH Royal Institute of Technology Research Field Computer science » Other Researcher Profile First Stage Researcher (R1) Application Deadline 1 Feb
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of advancing Swedish academia and industry to the forefront of quantum technology, and to build a Swedish quantum computer. The student contributes to this project to explore fundamental and applied questions in
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Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Do you want to work on enabling groundbreaking, data-driven Life Science
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at: https://www.umu.se/en/department-of-computing-science/ Project description and working tasks The project will develop privacy-aware machine learning (ML) models. We are interested in data driven models