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growth, electricity usage, and their implications for U.S. supply chains and energy infrastructure plans. The successful candidate will apply methods from economics, supply chain risk analysis, and data
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on developing a new hybrid light–matter platform that couples transition metal complexes with optical microcavities to achieve optical control over ultrafast spin conversion and charge transfer
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beyond the Standard Model, including effective field theories and perturbative QCD, phenomenology at current and future colliders, as well as emerging areas in Artificial Intelligence, Machine Learning
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frequencies Conducting end-to-end beam dynamics studies at full beam energy and current, including comprehensive error analyses using large-scale beam simulations Evaluating linac failure scenarios, defining
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/ML model development to design and discover redox-active materials with tunable properties (structure, charge state, etc.) Discovery of novel materials for energy storage and conversion and their
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, materials synthesis, and separation processes. Position Requirements Recent or soon-to-be-completed PhD (typically within the last 0–5 years) in chemistry, geochemistry, chemical engineering, physics
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simulation, TEA and LCA, and have a good knowledge of current and future resource recovery and separation technologies. The successful candidate will 1) collect data pertaining to battery recycling, battery
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PhD (within the last 0-5 years) in field of physics, chemistry, materials science, electrical engineering, or a related field Demonstrated expertise in electronic structure theory Experience with large
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, electrical engineering, materials science, or a related field at the PhD level with zero to five years of employment experience. Hands-on experience in one or more of the following: Cryogenic detectors (TES
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at Jefferson Lab Innovation in detector technologies such as 3D-printed pixelized MCP-PMTs and superconducting nanowire single-particle detectors Position Requirements Recent or soon-to-be-completed PhD (within