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thermal energy storage using a combination of molecular dynamics and process-scale simulations. By linking molecular-level understanding to engineering-scale performance, you will contribute
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of machine learning and advanced molecular dynamics techniques for molecular simulations and to study Nucleic acids structures and their interactions. For more information, please visit https://nyuad.nyu.edu
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. Position 1: Attosecond electron dynamics This position is part of the DOE-funded Early Career project "Rigorous quantum simulation tools for correlated attosecond electron dynamics in molecules." It will
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-of-the-art solid-state NMR techniques, including fast magic-angle spinning (MAS), proton-detected NMR, dynamic nuclear polarization (DNP), and multinuclear spectroscopy to investigate molecular structure
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robust, open-source implementations and connect the resulting models to nonadiabatic molecular dynamics simulation workflows. We’re here for the same mission, to bring science solutions to the world. Join
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molecular dynamics simulations, in close collaboration with leading European research institutes and steel industry partners. Job description At TU Delft, you will contribute to a transformative research
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pathways of atmospheric organic reactions. AI-augmented molecular simulations: developing and applying machine-learning force fields and state-of-the-art enhanced sampling to reveal interfacial and
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at the atomic scale, using density functional theory-accurate machine-learned potentials and molecular dynamics simulations, in close collaboration with leading European research institutes and steel industry
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postdoctoral researcher will develop and apply advanced simulation techniques, and data-driven approaches to explore complex biophysical phenomena at the cell membrane. This role provides a platform for
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, molecular weight and molecular-weight distribution, moisture and residual-acid content, and stability and energy content – and to lead a comparative measurement study (round-robin) between KTH, FOI and