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molecular dynamics, continuum non-equilibrium methods, and artificial intelligence assisted tools to simulate the aforementioned systems. Enhanced sampling methods and collective variable discovery
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teamwork. Applicants should have expertise in some of the following: Density functional theory/molecular dynamics modeling of materials, e.g. high throughput calculations, structure prediction, classical
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conduct fundamental research in chemical separations using computational methods, including free energy methods with molecular dynamics simulations. The position will focus on solution phase separations
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or classical molecular dynamics) of metal-inorganic complexes and clusters. Scientific programming (e.g. C++, Fortran, python,….) An understanding of basic concepts in deep learning and PyTorch will be a plus
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exascale architectures. The candidate will work with the electronic structure code WEST (http://west-code.org) and/or molecular dynamics code Qbox (http://qboxcode.org ) and will be also involved in using
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(density functional theory, ab initio or classical molecular dynamics) modeling of metal-organic complexes and clusters, under explicit and implicit solvent. 2) Scientific programming (e.g. C++, fortran
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of molecular reactions occurring at the surface of various materials. In addition, computational fluid dynamics (CFD) simulations combined with microkinetic modeling will be carried out to study the heat
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will use first principles modeling, molecular dynamics, and AI assisted methods to perform simulations/predictive analytics of materials and molecules to understand electrochemical processes and surface