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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 20 hours ago
sciences because it provides understanding of the forces governing the structure of matter, from subatomic particles to the large-scale structure of the universe. Our departmental instructional mission spans
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date is September 14, 2026. This position will be based on the Stanford campus. Project Description: Rebekah Dix , Technology, Provider Decision-Making, and Productivity in Healthcare This is a full-time
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Helmholtz programs. Structured doctoral training and international visibility: The PhD candidate will be part of the HDS-LEE graduate school, benefiting from a structured qualification program, dedicated
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-on training in quantitative policy research in economics. You will gain experience in: Working with large-scale and high-dimensional datasets Data construction, including web scraping Spatial analysis (e.g
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Your Job: At the Institute for Advanced Simulation – Data Analytics and Machine Learning (IAS-8) we are looking for a PhD student in machine learning to work within a project linked to the
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, energy systems, or material sciences A Masters degree with a strong academic background in mathematics, computer science, physics, material science, earth science, life science, engineering, or a related
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: Minimum MSc degree in Civil Engineering or Material Science applied to construction materials with minimum two years of industry experience. A PhD would be desirable. Skills/experience required include
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Your Job: At the Institute for Advanced Simulation – Data Analytics and Machine Learning (IAS-8) we are looking for a PhD student in machine learning to work within a project linked to the
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Your Job: We are looking for a PhD student to develop learning-based surrogate models for predicting stress fields in patient-specific arteries. Especially high stresses in plaque can lead to
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heavily relies on empirical determination of key model parameters. By combining protein structure descriptors, molecular simulations, and machine learning, this PhD project seeks to predict ion-exchange