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and transport systems, within the ELLIS network. The project is fully funded through the Novo Nordisk Foundation Data Science Distinguished Investigator programme. You will be based in the Intelligent
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academic approval, and the candidate will be enrolled in one of the general degree programmes at DTU. For information about our enrolment requirements and the general planning of the PhD study programme
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, journalism, political science, sociology, law, economics, or computational social science, as well as an interest in how AI transforms the media and information ecosystem. The PhD student(s) will be embedded
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of these materials. Implementation of artificial intelligence (AI) and machine learning (ML) to establish the connection between the existing models and material data (both literature and the baseline established in
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data. You will encode prior knowledge of the collisional processes in tokamak fusion plasmas using sophisticated numeric simulation codes, which will enable you to analyze data from tokamak experiments
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is a lively and research-oriented group of scientists and support staff with a broad interest in information processing in humans and computers, and a particular focus on the signals they exchange, and
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of demographic methods and experience with software such as R, or similar tools; be eager to learn new demographic methods. Further information about the position can be obtained from Head of Administration Astrid
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Job Description Are you passionate about environmental contaminants, food safety, marine ecosystems, and creating real-world impact through cutting-edge analytical and data-driven approaches? Do you
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comprehensive training in translational liver research, including data analysis, experimental design, and scientific dissemination. Qualifications We are looking for a highly motivated PhD candidate with a strong
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assessment. Design and train reinforcement learning agents to optimize operational safety. Build and validate dynamic Bayesian network models integrating empirical and synthetic data. Conduct scenario-based