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Field
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, by that enabling improved control and optimization. Stall detection will be a natural part. The PhD project is internally financed but will be associated to two large research programmes at NTNU and
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Inria, the French national research institute for the digital sciences | Rennes, Bretagne | France | about 1 month ago
The candidate should have strong background in image/signal processing, optimization and programming, notions of source coding, information theory would be appreciated. LanguagesFRENCHLevelBasic
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methodologies for evaluating suitable storage sites and optimized lined rock cavern designs; - publish research findings in leading international scientific journals; - present research at national and
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replication, pathogenesis, and host-fungi interactions to inform rational drug design and optimization of antifungal therapeutics. Collaboration and Project Management: Coordinate with multidisciplinary teams
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Monte-Carlo simulations to optimize the detector geometry, as well as in its testing and commissioning. It will include as well the preparation of forthcoming experiments at the DESIR facility in GANIL
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optimize the detector and its parameters. In this project, you will focus on developing a suitable solution for integrating photo detectors with the analog front-end. You will work on this solution, ensuring
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all children with cancer, with optimal quality of life. The center brings together the best possible care and scientific research, creating a unique interdisciplinary institute for pediatric oncology in
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experience in power electronics (10%) 2. Design and optimization of power supplies. (20%) 3. Modelling and control of power converters and energy conversion systems (DC Microgrids,…). (20%) 4. Digital control
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includes system operation, continued development, and performance optimization. The successful candidate will collaborate closely with the quantum metrology group at the University of Bonn and the geodetic
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optimization of machine learning methods for processing Quantum OCT (Q-OCT) signals. Design, training, and testing of neural network architectures for artefact and dispersion removal in Fd-Q-OCT and SS-Q-OCT