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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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key element of the two-beam acceleration concept Emphasize Bayesian optimization approaches and integrate these methods into the facility control system Design, execute, and analyze accelerator
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statistical analysis and modeling techniques such as Gaussian process modeling, data assimilation, and Bayesian analysis; and 4. Open-source scientific software development. Expertise in computational
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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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, including communication, networking, and leadership. Position Requirements To perform the essential functions of this position successful applicants must provide proof of U.S. citizenship, which is required
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present research in conferences. Network and develop collaboration with other groups and divisions internally and with other national labs, industry, and utilities. Position Requirements Recent or soon-to
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qubit-based quantum processors and connect them via a campus-scale fiber-optic network. The postdocs will design and fabricate superconducting transmon qubits and microwave-optical quantum transducers and
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evaluate distribution networks in OpenDSS; investigate feeder- and system-level impacts of DERs (e.g., load flow, hosting capacity, voltage regulation). Develop and refine T&D co-simulation platforms (e.g
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, networking, and leadership. Position Requirements Required Knowledge, Skills, and Experience: This level of knowledge is typically achieved through a formal education in economics, operations research, public
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experts across system software, power management infrastructure, performance characterization, networking, and novel computer architectures and accelerators. It will also involve collaboration with leading