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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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. This position offers an exciting opportunity to work at the intersection of HPC and AI, addressing critical communication bottlenecks and optimizing network interconnects for large-scale distributed systems
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or upcoming year (optional) Experience in one or more of the following areas: experimental data analysis related to hadronic physics, polarized targets or beams, silicon sensors, calorimetry, detector
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that affect wetland carbon dynamics Experience with relevant instrumentation and methodologies, such as flux chambers, CO2 / CH4 sensors/analyzers, gas sampling, and/or water sampling Experience and an interest
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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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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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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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, 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
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with physics-informed neural networks, automatic differentiation, neural ODEs, or other physics-aware DL techniques. Skill in programming languages such as Python, C/C++, Go, Rust etc. Ability to model