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an established code (for example VASP, Quantum ESPRESSO). ● Research experience performing molecular dynamics simulations. ● Experience training, fine-tuning, or validating machine-learning interatomic
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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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(including neural quantum states), stabilizer and near-Clifford simulation, Gaussian/free-fermion methods, open-system dynamics (Lindblad master equations). - Machine learning for physical systems: deep
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closely related quantitative field in hand by the start of the appointment. ● Demonstrated expertise in molecular dynamics simulation and enhanced-sampling techniques (e.g., Gaussian accelerated MD/GaMD
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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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design. The position will primarily investigate G protein-coupled receptors (GPCRs) involved in cardiovascular and hormone signaling pathways using computational approaches such as molecular dynamics
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dynamical-decoupling measurements of T1 and T2) and static-field ODMR magnetometry with standard transmon characterization and qubit-intrinsic noise spectroscopy (CPMG and spin-locking sequences) on the same
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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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of molecular dynamics simulation and mathematical modeling. Working Environment Laboratory and research environment. About The University of Texas at Tyler and UT Tyler Health Science Center The University
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 1 month ago
the molecular mechanisms responsible for the nuanced signaling paradigms of GPCRs and how they lead to vastly different biological outcomes. Gaining atomistic insights into receptor-ligand interactions will allow