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computational fluid dynamics (CFD) simulations of blood flow through arteries and develop a cutting-edge super-resolution framework using convolutional neural networks (CNNs). The ultimate goal is to vastly
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to apply): Prior research experience in plasma control, tokamak magnetic confinement fusion, or computational fusion science. Artificial Intelligence (AI), Machine Learning (ML), and Scientific Machine
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, Physics, Materials Science, or a related discipline. Strong background in condensed matter theory, electronic structure methods, many-body physics, and molecular simulations. Knowledge of magnetism and open
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at APCTP and partner institutes, and pursue independent research projects. ● Requirements: A PhD in theoretical/computational magnetism, condensed matter physics, or a closely related field is required by
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9546 Employee Class Acad Prof and Admin Add to My Favorite Jobs Email this Job About the Job The AURORA Lab at the University of Minnesota’s Center for Magnetic Resonance Research is seeking a
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systems these materials enable. We are interested in colleagues who make, scale, and integrate critical-material components, for example permanent magnets, battery electrodes, wide-bandgap semiconductors
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2026 Is the job funded through the EU Research Framework Programme? Other EU programme Reference Number PID2025-171686OB-C21 Is the Job related to staff position within a Research Infrastructure? No
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underwater trial using a sovereign quantum vector magnetometer. The objective of the project is to use the gathered survey data to explore advanced platform compensation techniques, map matching and magnetic
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. You will be part of an interdisciplinary team bridging the gap between machine learning and materials science to develop next-generation computing hardware based on nanoscale magnetic systems
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Description We work with scientists in other NIST laboratories to develop tools for computer simulation and analysis of magnetic systems at the nanometer scale. Model verification is achieved by comparison