43 machine-learning-"https:"-"https:"-"https:"-"University-of-St" PhD positions in Sweden
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application! We are looking for a PhD student for sustainable and resource-efficient machine learning. Your work assignments Machine learning has recently advanced through scaling model sizes, training budgets
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education to enable regions to expand quickly and sustainably. In fact, the future is made here. The Department of Computing Science at Umeå University is looking for a doctoral student in machine learning
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of machine learning which clearly integrates the two subject areas within the division. For more information about STIMA, please see https://liu.se/organisation/liu/ida/stima . Linköping University is
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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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education to enable regions to expand quickly and sustainably. In fact, the future is made here. The Department of Computing Science at Umeå University is looking for a doctoral student in machine learning
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an increased interest in adapting and developing the latest machine learning methods for the purpose of malware detection, and preliminary results are encouraging. The specific goals of this project include
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the subject of Machine Elements, where the research is primarily focused on tribology and its applications. The research group currently consists of about 40 researchers and doctoral students and is one
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research team, you get the chance to develop in tribology, work interdisciplinary and conduct research in close collaboration with industry. You will be working in the subject of Machine Elements, where
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education to enable regions to expand quickly and sustainably. In fact, the future is made here. Umeå University is offering a PhD position in Computing Science with a focus on machine learning for graph
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biomedical engineering, electrical engineering, machine learning, statistics, computer science, or a related area considered relevant for the research topic, or completed courses with a minimum of 240 credits