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; Selection Criteria Master degree in mathematics, computer science or a closely related field; Strong interest and demonstratable expertise in formal methods and/or quantum computing; Affinity with the field
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The Faculty of Science is a world-class faculty where staff and students work together in a dynamic international environment. It is a faculty where personal and academic development are top priorities. Our
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PhD candidate, Compliance by Design: Technical Challenges of EU AI Act Requirements and Their Ethica
Artificial Intelligence, Data science, Applied Mathematics, Computer science, or related field; Strong interest in ethics; Good programming skills in, e.g., Python; Credible experience with Machine Learning
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track record proven by relevant experience, publications, etc. The applicant is expected to have: MSc degree in Computer Science, Artificial Intelligence, Electrical Engineering, Applied Mathematics
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the Netherlands may be eligible for a substantial tax break. For more information, see the website . Faculty The Faculty of Science at Leiden University is a world-class faculty where staff and students work
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of the key challenges that our world faces. At the same time, reinforcement learning is a key technology in artificial intelligence and machine learning that set various state-of-the-art results. In
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world-class training to doctoral candidates (DCs) in EU ‘glocal’ counter-terrorism - thinking globally, responding locally; and (2) to generate scientific excellence and technological innovation in
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of the future. The research carried out at the Faculty of Science is very diverse, ranging from mathematics, information science, astronomy, physics, chemistry and bio-pharmaceutical sciences to biology and
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the domain of machine learning. For more information see: https://www.cddl.nl Research at our faculty The Faculty of Science is a world-class faculty where staff and students work together in a dynamic
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. Selection criteria Master's degree in a relevant discipline e.g. environmental or sustainability science, industrial ecology, environmental engineering etc. Good mathematical background Knowledge and interest