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functions to work properly. Please turn on JavaScript in your browser and try again. UiO/Anders Lien 1st March 2026 Languages English English English PhD Research Fellow in Machine Learning for Cognitive
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and might include a component of machine learning to speed up interpretation of the phage testing. The appointed candidate will be able to receive further technical guidance and supervisory support from
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improvements. Examples include optimizing the squeezing of the vacuum to minimize quantum noise, a prototype cryogenic interferometer, using machine learning for nonlinear feedback control, devising techniques
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interested in applicants who use advanced quantitative methods, including computational modeling, machine learning, and/or analyzing structural and functional neuroimaging data. Specific activities may include
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understand, explain and advance society and environment we live in. Your role The University of Luxembourg invites applications for a fully funded Ph.D. position in machine-learning force fields (MLFFs
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U.S. Department of Energy (DOE) | Washington, District of Columbia | United States | about 4 hours ago
science and technology to reduce risks and costs within the EM regulatory framework. The Scholar will participate in learning and development opportunities, be actively mentored by EM staff, as
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partners in the digital health and health delivery ecosystem. Research Responsibilities Responsibilities will vary depending on the Fellow’s background, but may include: • Developing machine learning
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VIB.AI, the VIB Center for AI & Computational Biology, is a young research center dedicated to combining machine learning with in-depth knowledge of biological processes. Our mission is to study
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, citizenship status, color, creed, disability, domestic violence victim status, ethnicity, familial status, gender and/or gender identity or expression, marital status, military status, national origin, parental
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Your Job: As part of an interdisciplinary project team with researchers from bioinformatics you will work on quantum algorithms for drug discovery. Here, the focus lies on machine learning and