895 computational-physics "https:" "https:" "https:" "https:" "Brookhaven National Laboratory" positions in Sweden
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. The application should be registered via Umeå University’s e-recruitment system Varbi (https://umustipendie.varbi.com/en/what:job/jobID:887298/ ) and submitted by the deadline 18 March 2026. Please apply at with
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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 related to staff position within a Research
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Deadline 30 Jan 2026 - 22:59 (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 Is the Job related to staff
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Profile Leading Researcher (R4) Application Deadline 18 Feb 2026 - 22:59 (UTC) Country Sweden Type of Contract Permanent Job Status Full-time Is the job funded through the EU Research Framework Programme
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: https://www.umu.se/en/work-with-us/benefits/ . The candidate’s physical workplace will be in Umeå, starting date March 1, 2026 or by agreement. Application You apply via our e-recruitment system Varbi
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researchers work on the entire scale from molecular mechanisms and microbiology to the structure, function and behaviour of animals, and how these are affected by breeding, physical activity, care, production
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Gaussian process regression to represent unknown dynamics for model predictive control. Despite the practical success, there are still many theoretical open questions regarding scalability, uncertainty
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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 - with focus on education and research Do you want to lead the development
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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 Division of Infection Medicine The research group in Structural Infection
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, where AI models are trained without having all data in a single computer. This makes it possible to use larger datasets for training, without sending sensitive data between hospitals. The goal is to