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more value with strong quantitative skills and some coding proficiency to accelerate the innovation process and help others leverage your work. As you get going, you’ll gain new knowledge and insight
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opportunities, but you can add even more value with strong quantitative skills and some coding proficiency to accelerate the innovation process and help others leverage your work. As you get going, you’ll gain
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Post doc position in theory of machine learning at Department of Computer Science, Aarhus University
years. The application deadline for the position is June 1st, 2025. Applicants should apply online via our recruitment system by sending a letter of interest and a CV, as well as indicate at least two
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for Studying Metabolic Plasticity (ECR 5) For further information please visit: https://www.umg.eu/en/potenziale-entfalten/ecr What we offer: Generous support (your own position, a postdoc (1.0), a PhD student
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of two Associate Professors, two Assistant Professors, a Lab Manager, a Center Administrator, and app 10-15 PhD students, postdocs and visiting scientists. Several POLIMA researchers have attracted
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, digital and mixed-signal integrated circuits Layout design for CMOS and OLED production Close cooperation with interdisciplinary departments and research partners (e.g. OLED technology and production
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Sintorn, Professor in digital image processing, at the Department of Information Technology and conducted alongside researchers developing computational methods with a particular focus on deep learning and
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real-world impact. We work across domains such as healthcare, automotive, and manufacturing, using multimodal data and foundation models. The team includes PhD students, postdocs, and industry
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methods based on optimal transport for addressing problems in signal processing, control theory, and inverse problems. The doctoral student project and the duties of the doctoral student By developing novel
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, implementation of methods in computer codes, use of state-of-the-art high-performance computers in Sweden and in Europe, application of machine-learning and AI techniques, and collaborations with experimental