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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
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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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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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) and with the Computer Vision Laboratory at the Department of Electrical Engineering (ISY), a world-class research environment specializing in machine learning, deep learning, and visual perception
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unique challenges from a machine learning perspective, calling for novel machine learning research that will push the boundaries beyond the current state-of-the-art. As a PhD student, you devote most
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the Higher Education Ordinance. To meet the general entry requirements for doctoral studies, you must: hold a Master’s (second-cycle) degree in engineering physics, electrical engineering, machine learning
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well as electrical flow. Prototyping of the identified structures via stereolithographic, 3D printing and textile techniques like tufting, machine-based embroidery techniques or non-interlaced 3D pre-forming
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identify optimal hierarchical shaped pore- and electrode-structure to encounter optimum electrolyte as well as electrical flow. Prototyping of the identified structures via stereolithographic, 3D printing
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description of current literature on which you would base your research, both methodologically and in terms of the concrete PhD topic. Your workplace The Department of Computer and Information
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superconductivity, mesoscopic phenomena and nanotechnology (for more info see http://ekmf.fysik.su.se ). The current project is focused on the development of future superconducting quantum electronics and