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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
modeling of large-scale dynamics in networks. This role involves creating large scale models of dynamic phenomena in electrical power networks and quantifying the risk of rare events to mitigate
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structural models and compute electronic and vibrational properties. Develop and train neural-network or other machine-learned interatomic potentials to enable large-scale molecular dynamics (MD) simulations
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-informed AI framework that decodes the complex relationships between material defects, functional fields (e.g., strain, electrostatic potential), and device performance, with a primary focus on leveraging
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(BCDI), Laue microdiffraction, ptychographic laminography, and X-ray photon correlation spectroscopy (XPCS) to study strain, dislocation networks, voids, and interfacial morphology. Develop in-situ and