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application! We invite applications for a fully funded PhD student position to join the research group of Jan Glaubitz to work on Bayesian Computational Mathematics for reliable and trustworthy uncertainty
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identify, analyze, and evaluate strategies that can make the last-mile distribution more sustainable than today. You will, for example, analyze different scenarios with mixed vehicle fleets, charging
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application! The position Linköping University has a new cybersecurity lab that includes both a computer room for students and a server environment that can be used to simulate different scenarios related
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application! We are looking for a PhD student in Statistics with placement at the Division of Statistics and Machine Learning, Department of Computer and Information Science. Your work assignments As a PhD
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NAISS, the National Academic Infrastructure for Supercomputing in Sweden, provides academic users with high-performance computing resources, storage capacity, and data services. NAISS is hosted by
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NAISS, the National Academic Infrastructure for Supercomputing in Sweden, provides academic users with high-performance computing resources, storage capacity, and data services. NAISS is hosted by
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world and a strong commitment to both WASP (Wallenberg AI, Autonomous Systems and Software Program) and ELLIIT (Excellence Center at Linköping – Lund in Information Technology). Read more about the division
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Deadline 31 Jan 2026 - 12:00 (UTC) Type of Contract Permanent 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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materials and technologies. Using advanced computational modeling and machine learning, we seek to elucidate the mechanisms governing the self-assembly of lignin in different solvents and the formation
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other departmental duties, up to a maximum of 20 per cent of full-time. Your qualifications You have graduated at Master’s level in Electrical Engineering, Computer Science, or Applied Mathematics, with a