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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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functional theory (DFT) outputs for representative quantum paraelectrics and use these force fields to perform lattice-dynamics simulations with explicit quantum mechanical treatment of the nuclei. Profile A
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mechanisms that dynamically alter the detrapping and recombination probabilities. The aim of this project is to overcome these limitations by developing a Monte Carlo simulation model that treats each charge
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) simulations or MD simulations based on DFT theory (e.g., Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS)), Machine-Learning potentials development (e.g., TorchANI, DeepMD) Preferred
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Swedish bedrock. The candidate will combine work with DFT codes, many-electron phenomena and spin dynamics methods. The key properties of our studies are magnetization, exchange interations, and
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-Rossendorf in Görlitz, Germany. This project aims to develop and apply novel, temperature-dependent approximations for electron-electron interactions using density-functional theory (DFT), with a specific
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localized and delocalized mechanisms that dynamically alter the detrapping and recombination probabilities. The aim of this project is to overcome these limitations by developing a Monte Carlo simulation
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purification. The postdoc will perform theoretical simulations of 3D/2D materials by primarily Density Functional theory (DFT), for identification of ground state crystal structure, composition and properties
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Computer simulations of radiation damage in crystalline and amorphous materials Molecular-dynamics simulations Density functional theory (DFT) calculations Time-dependent DFT calculations Atomistic
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 1 month 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