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superconductors. The successful candidate must have substantial experience in state-of-the-art ARPES and/or low temperature STM/STS techniques. Some experience with first-principle methods (FP/DFT) and/or other
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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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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
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simulation (classical and ab-initio molecular dynamics, DFT, simulations) Proficiency in programming languages like Python, C++, or Fortran for custom analysis tools. Experience in developing workflows
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quantum mechanical calculations (e.g., first principles density functional theory (DFT)) to identify the structures and to understand the complex mechanisms of molecular reactions occurring at the surface
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 17 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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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
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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