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of Science and Engineering, a 4-year interdisciplinary PhD position is available at the Bernoulli Institute for Mathematics, Computer Science and Artificial Intelligence. The candidate will become a member of
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of Science and Engineering, a 4-year interdisciplinary PhD position is available at the Bernoulli Institute for Mathematics, Computer Science and Artificial Intelligence. The candidate will become a member of
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of Science and Engineering, a 4-year interdisciplinary PhD position is available at the Bernoulli Institute for Mathematics, Computer Science and Artificial Intelligence. The candidate will become a member of
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of Science and Engineering, a 4-year interdisciplinary PhD position is available at the Bernoulli Institute for Mathematics, Computer Science and Artificial Intelligence. The candidate will become a member of
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associated with the spin-in of applied artificial intelligence to the space system domain; Designing and conducting representative capture-the-flag exercises, and in-orbit cyber exercise and technology
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GIS and spatial analysis Data science, data mining, and information retrieval (multi-modal) Machine learning, deep learning and artificial intelligence (Initial) Experience in grant acquisition and
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/ Robust) Combinatorial Optimization, Game Theory, and Network Theory, as well as Artificial Intelligence. Potentially, scenarios could be simulated using agent-based, discrete-event, or other techniques
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equivalent) in Computer Science, Data Science, Artificial Intelligence, Computational Social Science, or a closely related discipline. The ideal candidate has a strong interest in algorithms, machine learning
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research across a wide range of disciplines, from classical fields such as biology and mathematics to interdisciplinary areas like artificial intelligence, pharmacy, and nanoscience. The PhD position is
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applications* in close collaboration with other discipline experts (software, microelectronics and applications engineers). * except for RF payloads. ** including artificial intelligence and machine learning