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engineering, or a closely related field, in hand by the date of appointment. ● Research experience performing first-principles electronic structure or density functional theory calculations using
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materials, organic solids, molecular materials, or other solid-state systems. Experience with computational approaches relevant to structural characterization, including density functional theory (DFT
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Position Description POSTDOCTORAL POSITIONS IN CONDENSED MATTER THEORY, CALIFORNIA STATE UNIVERSITY NORTHRIDGE One postdoctoral position in Condensed Matter Theory is available in the group
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and machine learning with density functional theory, or other similarly relevant computational methods, to advance understanding of materials design predictions for 2D and 3D systems with electronic and
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the dissertation, must be completed by the date of appointment. Demonstrated research experience with density functional theory or closely related first-principles atomistic simulation methods. Demonstrated research
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: Postdoctoral Researcher - College of Engineering Position Type: Faculty Location: Villanova, PA Recruitment Type: Internal/External Applicants Work Schedule: full-time/12-months Department: 959-Center for Energy
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National Energy Technology Laboratory (NETL) | Pittsburgh, Pennsylvania | United States | about 9 hours ago
computational physics, chemistry, and materials science. Research experience involving density functional theory and ML simulations and is Familiarity with software packages such VASP, CP2K, Gaussian, Scikit
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National Energy Technology Laboratory (NETL) | Morgantown, West Virginia | United States | about 9 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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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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, 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