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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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methods at the density-functional and dynamical mean-field-theory levels, metal-insulator and structural phase transitions, quantum critical points, nonlinear and anomalous responses, optical traps, quantum
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to) SIESTA (www.siesta-project.org) and its TranSIESTA functionality. SIESTA is a multi-purpose first-principles method and program, based on Density Functional Theory, which can be used to describe the atomic
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. Demonstrated experience in performing simulations at the atomic-scale, such as density functional theory (e.g. VASP, Ab-init, Quantum espresso), molecular dynamics (e.g. LAMMPS, DL-POLY), development of inter
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deposition (ALD). The project involves performing quantum mechanical calculations (e.g., first principles density functional theory (DFT)) to identify the structures and to understand the complex mechanisms
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to apply. We seek candidates with expertise in some or all the following areas: density functional theory, deep learning, high-throughput simulations, molecular dynamics, and materials chemistry. Strong
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the group’s research and philosophy head over to www.d2r2group.com Qualifications Strong background in ab-initio calculations of materials (density functional theory) and high-performance computing
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the group’s research and philosophy head over to www.d2r2group.com Qualifications Strong background in ab-initio calculations of materials (density functional theory) and high-performance computing