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National Energy Technology Laboratory (NETL) | Morgantown, West Virginia | United States | about 5 hours ago
Organization National Energy Technology Laboratory (NETL) Reference Code NETL-PIP-2026-Shekhawat How to Apply A complete application consists of: An application, including academic history, work
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of Prof. Georg Madsen, with regular shorter research stays at Aarhus University. The project combines density functional theory (DFT), machine-learned force fields and atomistic simulations to uncover how
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position within a Research Infrastructure? No Offer Description Activities and context: The fellow will develop machine-learning interatomic potentials (MLPs), trained on density functional theory-DFT data
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will participate in conducting multiscale modeling such as quantum mechanics density functional theory calculations, molecular dynamics simulations, Monte Carlo simulations, and/or machine learning
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theoretical research on magnetic and topological properties in van der Waals materials using Density Functional Theory (DFT) calculations, tight-binding and machine learning methods. Provide theoretical
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language models, reinforcement learning, agent learning, robotic control; (4) quantum materials simulation, density functional theory, catalysis and transition-state theory, molecular dynamics; (5
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, or foundation models. Familiarity with atomistic simulations (e.g., density functional theory, molecular dynamics). Interest in developing broadly applicable machine-learning methods for physical sciences
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highly desirable. Experience with computational methods such as density functional theory calculations, geometry optimization, and prediction of NMR parameters will be considered an advantage
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. An ideal candidate should have experience in modeling electrochemical reactions on surfaces and interfaces using first-principles density functional theory (DFT), grand canonical DFT (GC-DFT
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well as with theoretical researchers specializing in atomistic simulation, density functional theory (DFT), and ab initio molecular dynamics (AIMD). The successful candidate will also engage with collaborators