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combines: Fluid dynamics and heat transfer (theory and experiments), Computational modeling, and Machine learning / computer vision for data analysis and pattern recognition. The goal is to improve
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well as digital filters is advantageous. Your workplace You will be working at the Division of Electronics and Computer Engineering (ELDA), which conducts teaching and research in a broad range of areas, from
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general. Computer vision can also be included if there is interest. The graduate school within WASP is dedicated to provide the skills needed to analyze, develop, and contribute to the interdisciplinary
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theoretical analysis, 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
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by combining state-of-the-art computer simulations, physical experiments, and clinical studies in radiology departments at the hospitals in the region. You will work in a multi-disciplinary team and
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or more (with none of the sections scoring less than 5.0) • TOEFL score of 550 or more (computer based test 213, internet based 79) • Cambridge/Oxford - Advanced or Proficiency level. Selection
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collaboration with the Materials Design Division (also at IFM) and with the Computer Vision Laboratory at the Department of Electrical Engineering (ISY), a world-class research environment specializing in
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flow behavior. The project also involves applying machine learning and computer vision techniques to enhance data analysis, pattern recognition, modeling, and prediction. The role requires a solid
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-ray computer tomography. The position will be open at the Fluid Dynamic division of Mechanical and Maritime Science department. The research at the Division covers turbulent flow (both compressible and
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multiphase flow behavior. The project also involves applying machine learning and computer vision techniques to enhance data analysis, pattern recognition, modeling, and prediction. The role requires a solid