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Field
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Conduct comparative benchmarking and performance analysis against state-of-the-art studies Perform numerical modeling and validation of brain-inspired and neuromorphic algorithms Design, set up, and operate
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a PhD student, you will develop state-of-the-art learning and inference methods to detect and characterize anomalous radio behavior and to design algorithms that remain reliable under practical
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a PhD student, you will develop state-of-the-art learning and inference methods to detect and characterize anomalous radio behavior and to design algorithms that remain reliable under practical
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. The PhD students will work on several tasks, including: development of safe data-driven control/reinforcement learning algorithms to recover parameter identifiability by exploration of different
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in marine cybernetics Background in marine hydrodynamics Background in the application of probabilistic methods Experience with the application of AI algorithms Good programming skills Personal
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algorithms and methods for calibrated Bayesian federated learning for trustworthy collaborative Bayesian learning on data from multiple participants. The project will develop new methods, theory, and
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, evaluate and describe novel algorithms for learning concepts with theoretical guarantees from unstructured data; present research results at international conferences, workshops, and journals; pursue and
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algorithms. This is an exciting multidisciplinary PhD project that promises to make cutting-edge advances in all research areas involved. Aim This project combines practical hands-on optics experimentation
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of diagnostic and prognostic algorithms. Electronic Prognostics Systems: Facilities equipped to assess the health and predict the remaining useful life of electronic components, supporting studies in electronic
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molecular biology techniques as well as in algorithms, statistics and artificial intelligence for molecular genetics. Importantly, mastery of the experimental and theoretical aspects shall equip doctoral