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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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of experimental quantum communication hardware development, optical memory qubit characterization, and fiber-based networking demonstrations using novel memory qubits. The goal is to employ the natural telecom
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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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Biology: Strong background in systems biology and regulatory network modeling Interdisciplinary Collaboration: Experience working across disciplines with computational biologists, computer scientists, 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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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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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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model classifiers (PLS-DA, random forest, neural network, etc) towards unraveling materials structure-function relationships, and are familiar with optimization approaches such as genetic search, Bayesian
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. Understanding of high-order methods for fluid flows. Understanding of turbulence, boundary layer flows, multi-phase flows, chemical kinetics, combustion, and detonations. Experience in mesh generation with
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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