426 computer-programmer-"https:"-"CNR" "https:" "https:" "https:" "UCL" uni jobs in Sweden
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of Excellence. The Department of Historical, Philosophical and Religious Studies invites applications for the doctoral training programme in philosophy. The Department of Historical, Philosophical and
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components Qualifications Basic understanding of physics, electronics and electrical equipment Computer skills in excel and/or Matlab Fluent in written and spoken English Ability to take initiative, be
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advanced levels, mainly within the agronomy- soil & plant programme, and is also active in courses for professionals. Together with a research group from the Department of Applied Animal Science and Welfare
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(R1) Application Deadline 19 Mar 2026 - 22:59 (UTC) Country Sweden Type of Contract Temporary Job Status Part-time Is the job funded through the EU Research Framework Programme? Not funded by a EU
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the Stockholm Environment Institute and Energikontor Syd. Work duties You will primarily devote yourself to your doctoral programme, which includes participation in research projects as well as third cycle
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Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description We
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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 related to staff position within a Research Infrastructure? No
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in “Sustainable Metal Recovery—Hydrometallurgy & Circular Economy” within the framework of Doctoral Research School Program—BioGeoMetals, funded by the Swedish Research Council. Subject description
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for this job through MathJobs.Org right now. Please apply at https://lu.varbi.com/en/what:job/jobID:901260/iframeEmbedded:0/where:4 . Contact: Eskil Hansen Email: Postal Mail: Lund University Centre
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program and have experience in applied artificial intelligence, data engineering, and programming. You should be interested in working across the entire machine learning pipeline. Since part of the work