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molecular dynamics simulations across multiple resolutions, most likely from the atomistic to the coarse grained level, using a variety of force fields and computational methods. Run large-scale simulations
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computational methodologies, ranging from atomistic and electronic-structure–based materials modeling and characterization, via machine-learning and high-throughput methods, to ab initio calculation
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methods to simulate between functional chemically active surfaces and molecules/liquids. Central methodologies include: static DFT calculations; TBMD and AIMD; classical atomistic and coarse-grained
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the study of nucleation mechanisms, the analysis of out-of-equilibrium energy and thermodynamic balances, and the validation of results by comparison with experimental data and atomistic simulations
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of residuals at the atomic scale and how they interact with other alloy additions, with migrating and transforming boundaries. This grant will bring together atomistic modelling (at Imperial College), atomic
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biophysics/chemistry/physics and related fields Experience with Molecular Dynamics using coarse grained or atomistic models Advantage is experience with simulations of disordered proteins/polymers and
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) Requirements for candidate: MSc in computational biophysics/chemistry/physics and related fields Experience with Molecular Dynamics using coarse grained or atomistic models Advantage is experience with
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and Simulation Group at ICN2 conducts cutting-edge research in computational materials science, focusing on electronic structure methods, atomistic simulations, and multiscale modelling. The group
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, particularly machine-learned interatomic potentials, in the context of chemical research. Knowledge of atomistic and coarse-grained classical force fields. Experience creating and maintaining scientific software
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) with DFT atomistic simulations to investigate the electronic structure and defect states in wide bandgap semiconductor nanomaterials. The goal is to better understand and optimize function