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-learning trained using the van der Waals corrected hybrid density functional theory (DFT) enabled SeA approach [J. Chem. Theory Comput. 19, 4182 (2023)]. The SeA approach is an accurate and efficient high
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techniques. The research will integrate ab initio-based modeling and DFT calculations with experimental data to enhance the understanding and optimization of the proposed materials as sorbents or possible
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 8 hours ago
materials research group led by Dr. Mengen Wang is seeking a postdoc researcher to work on computational materials and machine learning-driven materials discovery. The postdoc researcher will perform DFT and
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proficiency in Density Functional Theory (DFT) and/or Molecular Dynamics (MD) simulations, enabling the computational investigation of material properties, electronic structure, and atomic-scale behavior
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assemblies, ideally with a focus on battery materials. Demonstrated proficiency in Density Functional Theory (DFT) and/or Molecular Dynamics (MD) simulations, enabling the computational investigation