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partitions of unity that are unavailable in the analytic setting. We expect to apply these techniques to geometry, quantum mechanics, and other fields in mathematical physics. The project will be supervised by
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guest researchers of the research facility of HFML-FELIX (maximum of 10% of your time). This project aims to bridge fundamental physics of two-dimensional semiconductors with next-generation
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degree in computer science, mathematics, statistics, physics or relevant fields. Strong background in machine learning, preferably experience in probabilistic modeling, Bayesian machine learning, or graph
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candidate is encouraged to discuss and collaborate with (experimental) researchers at QuTech, as well as the Delft office of the UK company Riverlane. Requirements Master degree in physics or quantum
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are looking for a dynamic, serious, and motivated researcher with a Master degree in Geoecology, Geochemistry, Environmental/Organic Chemistry, Geoscience, Physical Geography, Landscape Ecology, Environmental
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criminal law. You will draw up a research plan and corresponding research methods in consultation with your supervisors and undertake the necessary administration for a smooth PhD process. You will conduct
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PhD: Characterization of subsurface heterogeneity in backward erosion (piping) Faculty: Faculty of Geosciences Department: Department of Physical Geography Hours per week: 32 to 40 Application
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diseases of the eye. You will work at the intersection of mathematics, physics, AI, and clinical practice through careful design and production of optical metasurfaces, which can help to correct macular
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states. Your profile The position is suited for highly motivated students interested in experimental condensed matter physics, nanoscience, and quantum materials. Candidates should hold a Master’s degree
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machine learning, medical imaging, and security venues and journals. Your profile Master's degree in computer science, physics, electrical engineering, mathematics, or a related quantitative discipline