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properties of Li-rich three-dimensional materials for lithium battery cathodes using density functional theory (DFT), molecular dynamics, cluster expansion, machine learning computational techniques. This work
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required. Who You Are (skills and experience): A PhD in chemistry, physics, materials science or a related discipline, and/or relevant work experience. Demonstrated expertise in density functional theory
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characterization, Density functional theory of dielectrics, Polymer synthesis, and fabrication High voltage phenomena Interested applicants should submit a CV and three journal publications. BACKGROUND CHECKS
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related field are particularly encouraged to apply.We seek candidates with expertise in some or all the following areas: density functional theory, deep learning, high-throughput simulations, molecular
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behavior within the storage system to optimize design and performance. Demonstrated proficiency in Density Functional Theory (DFT) and/or Molecular Dynamics (MD) simulations, enabling the computational
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advanced characterization methods of inorganic materials and their assemblies, ideally with a focus on battery materials. Demonstrated proficiency in Density Functional Theory (DFT) and/or Molecular Dynamics
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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
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using molecular mechanics and hybrid QM/MM methods. Applying density functional theory, correlated wavefunction methods (e.g., MP2, CCSD(T)), and multiconfigurational approaches (e.g., CASSCF, CASPT2
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related field are particularly encouraged to apply.We seek candidates with expertise in some or all the following areas: density functional theory, deep learning, high-throughput simulations, molecular