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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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evaluate advanced algorithms for applications such as secure and adaptive control, anomaly and attack detection, resilient decision-making, and AI-enabled operational support for highly distributed grids
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The Center for Energy, Environmental, and Economic Systems Assessment (CEEESA) works on innovative research to enhance the resilience, efficiency, and affordability of power grids. Advanced
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energy goals. ESIA also develops, deploy, and advance grid technologies that ensure a robust and secure U.S. grid transmission and distribution system. We collaborate with government agencies as
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
, large-scale computational science, and simulation of networked physical systems Familiarity with techniques for sensitivity analysis and handling high-dimensional problems Experience in power grid
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systems, and grid reliability. Knowledge of how AI-driven energy demand intersects with clean energy deployment, transmission expansion, and supply chain vulnerabilities. Ability to design and deploy data