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methods with optimization and decision-support models. Background in one or more of the following: time-series analysis, neural networks, forecasting, uncertainty quantification, sensitivity analysis
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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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, and cyber-resilient operation of distribution systems and networked microgrids. The successful candidate will contribute primarily to the control and cybersecurity thrusts of a multi-institutional
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The Nuclear Technologies and National Security (NTNS) Directorate is seeking a highly qualified and motivated Postdoctoral Researcher specializing in energy economics and supply chain analysis, with
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materials, while having the opportunity to shape a new research capability with broad impact across quantum networking, communications, and computing. Research Focus Design and fabricate superconducting
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novel machine learning models—including Physics-Informed Neural Networks (PINNs), variational autoencoders, and geometric deep learning—to fuse multimodal data from diverse experimental probes like Bragg
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specializing in energy economics and supply chain analysis. This role is pivotal in evaluating the economic competitiveness of the U.S. in the production and manufacturing of energy-related materials and
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to assess evolving risks in coastal-urban regions. Other key responsibilities include: Mesh design and high-resolution data utilization. Develop and refine high-resolution barotropic ocean meshes along U.S
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in the cleanroom at the Center for Nanoscale Materials. The candidate will work in a collaborative environment including a network of leading researchers. Position Requirements Recent or soon-to-be
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Biology: Strong background in systems biology and regulatory network modeling Interdisciplinary Collaboration: Experience working across disciplines with computational biologists, computer scientists, and