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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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for machine learning, e.g. through Berzelius as well as powerful local computers. You will work at the Division of biomedical engineering IMT , which conducts research within many different projects connecting
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collaborate effectively while contributing to multiple ongoing projects. Above all, you can work harmoniously with diverse team members with different backgrounds and levels of experience and are willing
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will be admitted to the program for doctoral studies. More information about the doctoral studies at each faculty is available at Doctoral studies at Linköping University The employment has a duration of
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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! 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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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
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2026 - 12:00 (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 position within
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and significant piece of information to the right point of computation (or actuation) at the correct moment in time. To address this challenge, you will focus on developing theoretical and algorithmic
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. Computational tools for simulating such processes - both traditional based e.g. on computational fluid dynamics and more recent based on AI/machine learning - constitute fundamental scientific domains that act as