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accordance with a set individual study plan. The focus will be on performing research to optimize and test DBTMI by combining state-of-the-art computer simulations, physical experiments, and clinical studies
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facilitate data sharing among actors involved in a new circular flow of flat glass. Within the project, two PhD students, one at the Department of Computer and Information Science (with computer science
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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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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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verifiability for AI systems, based at the Department of Computer and Information Science. These positions are funded by the Wallenberg AI, Autonomous Systems and Software Program (WASP). Wallenberg AI
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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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. Within the project, two PhD students, one at the Department of Computer and Information Science (with computer science, or possibly design or cognitive science as main subject) and one at Tema Technology
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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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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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requirements for doctoral studies, you must: hold a Master’s (second-cycle) degree in engineering physics, electrical engineering, machine learning, data science, computer vision, computer science, applied