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well as the programmes in statistics, cognitive science and innovative programming. Read more at https://liu.se/ida The position is based at the Division of Statistics and Machine Learning (STIMA). We conduct research
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decentralized machine learning. Welcome to read more about us at: https://liu.se/en/organisation/liu/isy/ks . For more information about working at ISY, please visit: https://liu.se/en/article/open-positions
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qualifications For this position we are looking for someone who have completed a degree at Master’s level in Electrical Engineering, Computer Science, or Applied Mathematics, with a minimum of 240 credits of which
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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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Technology (ITN) which is known for its activities in logistics, visualization and organic electronics. We combine academic height with fruitful collaboration with the surrounding society. The position
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/organisation/liu/isy/ks . For more information about working at ISY, please visit: https://liu.se/en/article/open-positions-at-isy . You will become a key member of a dynamic and ambitious research team across
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: https://liu.se/en/article/open-positions-at-isy . The employment When taking up the post, you will be admitted to the program for doctoral studies. More information about the doctoral studies at each
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Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Horizon 2020 Is the Job related to staff position within a Research Infrastructure? No Offer Description
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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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-scale neural network models. While the developed methods will be broadly applicable, particular emphasis will be put on the problem of inferring gas dynamics in urban environments. Gas dynamics shape air