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density functional theory, or effective interactions Knowledge of high-performance computing methods. Familiarity with neutron star physics and astrophysical simulations. The duties, qualification
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characterization with advanced computational chemistry tools, including molecular dynamics, density functional theory and Grand Canonical Monte Carlo simulations. Position Requirements A recent or soon-to-be
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build using molecular dynamics, the MACE foundation models and density functional theory. Main Tasks and responsibilities: AI4LSQUANT aims to accelerate quantum modelling by learning fast, accurate
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Physics, Materials Science, Chemistry, Chemical Engineering, Applied Physics, or a closely related field with a focus on computational materials modeling. Density Functional Theory (DFT) for surfaces and
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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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analytical skills, precision, reliability, understanding and knowledge of research theory. Basic field work skills necessary. Mental Requirements Initiative: takes ownership, does what is needed without being
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experimental probes as neutron and X-ray scattering, as well as solid state NMR and computational approaches including density functional theory calculations. The direct access to these facilities and
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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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recent or future doctoral degree recipient interested in conducting research supporting the mission of the U.S. Department of Energy's (DOE), Office of Science, Fusion Energy Sciences research 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