56 machine-learning "https:" "https:" "https:" "U.S" positions at University of Copenhagen in Denmark
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data management and machine learning is also preferred. An interest in energy system topics such as the green transition, sustainable energy systems, digital energetics etc. is preferred. Experience
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mathematical, statistical, and machine-learning-based analysis of complex data sets, such as hypothesis testing, supervised/unsupervised learning, linear models, etc. Experience with atlas-scale single-cell data
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(DInSAR). Minute surface uplift and subsidence signals will be automatically detected using machine-learning workflows, enabling systematic, user-independent identification of drainage events every 6–12
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, grant applications, and research management such as supervision and training of research fellows and other staff. The successful applicant must also teach, supervise, prepare and participate in
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supervision and training of research fellows and other staff. The successful applicant must also teach, supervise, prepare and participate in examinations, and fulfill other tasks requested by the Department
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, 2027. We are looking for students who are eager to teach and interested in developing both academically and as educators. We expect to hire TAs for the following courses. Since we may receive multiple
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project, should contact Principal Investigator prof. Mikkel Bille, mbille@hum.ku.dk , phone +45 35329480 Link to the department’s website: https://saxoinstitute.ku.dk Introduction PhD studies consist
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of Health & Medical Sciences at the University of Copenhagen, commencing as soon as possible. Information on the department can be found at: https://bmi.ku.dk/english/about_department/ Information
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working with large collaborative code projects Proficiency in applying AI-driven algorithms (e.g., neural networks, reinforcement learning) for the creation of surrogate models and the autonomous
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, please contact the principal supervisor Anne Sofie Hammer. General information about PhD study at the Faculty of Health and Medical Sciences is available at the Graduate School’s website: https