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control in the cultivation of grass seed. The project is funded by GUPD and Frøafgiftsfonden. Helping with computer vision tasks in other SDU UAS projects like WildDrone and GENIUS will also be part of
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. The project is based on the novel application of formalisms, algorithms, and computational methods from computer science to the modeling of microbial communities, for use in health science. We aim to expand
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to engage in pioneering research, collaborate with a large, dynamic and multidisciplinary team, and advance the field of quantum computing through innovative algorithms and technologies. This is an exciting
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, distributed algorithms, secure multiparty computation, and information theory. You are expected to speak and write in English at an academic level, and preferable also in Danish. Qualification requirements
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thus including sensing systems, tool condition features selection, algorithms for automated signal preprocessing, feature extraction and decision making based on ML and AI. An integral part of
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achieve automated data driven optimization (in terms of time and quality) of polishing process parameters by application of machine learning algorithms, leading to a robust, repeatable and fast polishing
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contributing to developing and implementing novel algorithms at the intersection of computational physics and machine learning for the data-driven discovery of physical models. You will be working primarily with
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enable the development of fault-tolerant quantum computing hardware and quantum algorithms that solve life-science-relevant chemical and biological problems. Within NQCP we are currently pursuing several
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research in innovative algorithms for the analysis and interpretation of medical image data to support computer-aided disease diagnostics and intervention planning. have an established track record
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PhD Stipends within Distributed, Embedded and Intelligent Systems (DEIS) At the Technical Faculty of IT and Design, Department of Computer Science, one PhD stipend is available within