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application! We are now looking for a PhD student in Computer Vision and Learning Systems at the Department of Electrical Engineering (ISY). Your work assignments Your task will be to analyse and adapt vision
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image processing and physics-informed machine learning? Would you like to work together with competent and friendly colleagues in an international environment? Are you seeking an employer that offers safe
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increasingly rely on data-driven models to extract, represent, and interpret information from complex and evolving environments. Traditional machine learning approaches, as well as many classical signal
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is linked to the ELLIIT project New Machine-Learning Methods for High-Dimensional, Population-Scale Health Data , conducted in collaboration with Lund University. The project aims to develop and apply
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application! Your work assignments Spatio-temporal processes are everywhere in science and engineering, with applications ranging from weather prediction to cardiovascular medicine. Developing machine learning
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expertise from control theory, machine learning, optimization, and network science, spanning diverse application domains such as energy systems, biomedical systems, neuroscience, and safety and security
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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
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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
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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