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on the development of hybrid QM/MM methodologies, machine learning approaches, and advanced free energy simulation methods. These methods are applied to investigate enzyme catalysis, conformational dynamics
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molecular dynamics simulations, applicable to materials science, biomolecules, or a related field. Programming experience (e.g., Python), with a strong background in developing and applying computational
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of persistent quantum entanglement. Essential Duties and Responsibilities: The successful candidate will operate in a friendly and dynamic team environment of the Condensed Matter Theory Group, with opportunities
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CFD methods DFT and Molecular modelling linked to CCUS Strong analytical and problem-solving skills, with an ability to interpret and analyze simulation and/or experimental results. Ability to work in
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functional inversion. Additional applications are possible on quasi-exact nonadiabatic nuclear dynamics simulations using tensor network states (ML-MCTDH) of vibronic coupling models. Of particular interest
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 1 month ago
to work on accelerated molecular simulations and AI-driven drug discovery. Research projects in the Miao Lab include development of novel theoretical and computational methods and AI techniques