877 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "U.S" "U.S" positions in Sweden
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June 2026, UFV-PA 2026/581 Where to apply Website https://uu.varbi.com/en/what:job/jobID:908266/type:job/where:39/apply:1 Requirements Research FieldMedical sciencesEducation LevelPhD or equivalent
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working at SLU by visiting: https://www.slu.se/en/about-slu/work-at-slu/ Location: Grimsö wildlife research station Form of employment: Fixed-term employment for 4 months, with a possible extension. Scope
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description Description of work You will be working in the laboratory of Marta Bally ( https://ballylab.com/ ), in close collaboration with the laboratory of Anne-Marie Fors Connolly ( https://www.umu.se/en
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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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solutions across the natural sciences. Your workplace You will be employed at the Department of Mathematics in the Division of Applied Mathematics, https://liu.se/en/organisation/liu/mai/tima . The research
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experience) of their research career and must not have been awarded a doctoral degree. Where to apply Website https://umu.varbi.com/en/what:job/jobID:907734/ Requirements Research FieldBiological
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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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employees and is characterised by a friendly, inspiring and international atmosphere, with a large number of employees from all over the world. The PhD student will be included in Machine- and Materials
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today and in the future. For more information: http://www.slu.se/en/departments/forest-ecology-management/ Read more about our benefits and what it is like to work at SLU at https://www.slu.se/en/about
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complex behavior under demanding operating conditions presents a significant modeling challenge. This project addresses that challenge by combining machine learning with constitutive modeling, while