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Field
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learning for materials discovery or quantitative image analysis, DFT calculations for catalyst design, experiences with MATLAB / Python / AutoCAD / COMSOL • Organic synthesis, polymer chemistry, synthesis
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, ideally molecular dynamics and/or DFT. Scientific programming skills, particularly in Python, are expected. Familiarity with machine learning or generative AI methods applied to materials would be a strong
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Chemistry or Material Sciences Specific Requirements · Knowledge of electrochemical processes. · Experience in materials simulation. · Knowledge of electronic structure methods (DFT, GW, etc.). · Previous
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to density functional theory (DFT) calculations and the generation of high-quality atomistic datasets for the development of analytical bond-order potentials (ADP) and machine-learned interatomic potentials
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, for DFT activities Where to apply E-mail [email protected] Requirements Research FieldEngineering » Materials engineeringEducation LevelPhD or equivalent Skills/Qualifications The ideal
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of solid-state materials, with experience in density functional theory (DFT) and/or machine learning interatomic potentials. We welcome applicants with a broad range of research interests and experiences who
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Eligibility criteria Skills: • Strong knowledge of theoretical chemistry methods (DFT, MD, ab initio). • Experience with molecular modeling software (e.g., MOLPRO, DeMon2K). • Interest in interdisciplinary
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 1 month ago
laboratory safety protocols. Strong written and oral communication skills and a record of scientific writing. DFT/MD modeling expertise. Familiar with Python and Linux Special Physical/Mental Requirements
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, please contact Duy Le at [email protected]. Responsibilities: The Postdoctoral Associate’s Responsibilities include but are not limited to: Performing computational modeling using DFT, GC-DFT, MD (AIMD
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-binding and DFT-derived (Wannier) Hamiltonians. Validate the extended theory on benchmark van der Waals heterostructures and interface the results with the AUTOMATA and COMPASS workflows. Publish the