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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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specifically on developing machine learning-based surrogates and emulators for the dynamics of power grids. This role involves creating advanced probabilistic models that capture the complex behaviors
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integrating scientific data from diverse sources, including numerical tables, text, and images. Design and implement LLM guardrails to enhance the reliability and accuracy of model outputs in scientific
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or soon-to-be-completed PhD (typically completed within the last 0-5 years) in Electrical Engineering Fundamental understanding of power system modeling, numerical methods and linear control theory
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at the APS, integrating x-ray optics and wave propagation models with realistic sample simulations based on dislocation dynamics and molecular dynamics of relevant materials. Significant attention needs
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The Nuclear Science and Engineering (NSE) Division is seeking a postdoctoral appointee to develop computational methods and computer codes to model the physics and engineering of advanced nuclear
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calculations, reactive empirical force fields, chemical dynamics, deep learning and numerical algorithms, data analysis, experimental characterization and imaging. Our research has involved methodology and
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candidate will engage in programs involving expertise in thermal-hydraulics modeling, chemical reaction engineering, electrochemical systems, system analysis, and advanced energy conversion systems
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candidates will engage in programs involving expertise in thermal-hydraulics modeling, chemical reaction engineering, electrochemical systems, system analysis, and advanced energy conversion systems