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numerical analysis, computational fluid dynamics, and uncertainty quantification with diverse applications. Our group maintains active collaborations with other divisions at Linköping University and broader
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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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Computational Physics and Biological Imaging comprises research in computational methods for structural biology, image reconstruction, and data-driven modeling of biological systems. The Division carries out
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at Master’s level in Computer Science, Electrical Engineering, or Applied Mathe- matics with a minimum of 240 credits, at least 60 of which must be in advanced courses in Computer Science, Electrical
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equations. Your main research assignments will be to develop new models and methods for generative sampling and Bayesian inference. You will be jointly supervised by Assistant Prof. Zheng Zhao (https
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2026 - 12:00 (UTC) Country Sweden 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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application! Your work assignments We are looking for a PhD student to work on the development of novel spatio-temporal machine learning methods. Our world is inherently spatio-temporal, i.e. physical processes
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will build an experimental and computational platform based on 3D-printed, brain-mimetic tissue models with tunable transport properties, where interface transport can be measured and predicted
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research at LiU focuses on securing the most critical functions of digital society. Through numerous national and European projects, methods are developed for areas such as verification, intrusion detection
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the Cybersecurity division where the research focuses on securing the most critical functions of digital society. Through numerous national and European projects, methods are developed for areas such as verification