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is subject to 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
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, reviewing of literature, experimental work, modelling, data analysis, writing etc. The project can to some extent be tailored to the candidate’s interests and expertise. The PhD student will follow courses
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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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of the jobpost. Further information Read more about our recruitment process here. The assessment of candidates for the position will be carried out by qualified experts. Shortlisting will be applied. This means
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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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candidate is expected to hold: A master degree in biomedical engineering or computer science, Excellent programming skills (Python). Experience with data curation, large-scale datasets, and machine learning
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properties through computer simulations. The project also includes validation of materials in the lab and translating the findings into practical recommendations for use in real power-electronics environments
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data availability and design parameters. Importantly, the AI implementation should act as a facilitator of creativity, enhancing, and inspiring the early design phase rather than constraining
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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
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; mepage.faculty.ucdavis.edu ). Simonsen will be the main advisor to the PhD student. Her research studies policies that directly or indirectly affect children’s outcomes and she is an expert on the Danish administrative data