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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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application! We are looking for a PhD student in biomedical engineering with a focus on deep learning for medical images Your work assignments The position focuses on developing methods for federated learning
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application! We are looking for a PhD student in Statistics and Machine Learning Your work assignments We are looking for a PhD candidate to work in the intersection of computational statistics and machine
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protein levels. Experience with stem cells, in vivo models and systems, microsurgery and/or computational methods are not strictly required but are considered as an asset. You are proactive and driven, able
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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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. The focus will be on developing and automatically learning new methods for efficiently solving planning tasks. The projects will involve both theoretical and experimental work. Qualifications To be qualified
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, or has experience with optimization algorithms and with improving the efficiency of computational methods. The workplace Linköping University is one of the leading AI institutions in Sweden. We have strong
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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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of grief, and whether the experience of loss changes how individuals view their own mortality. The subprojects will use multiple methods, including qualitative analyses, questionnaires, functional magnetic
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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