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nuclear theory, low-energy nuclear physics, medium-energy nuclear physics, fundamental interactions, and accelerator technology, with additional smaller-scale programs in optical trapping of atoms, quantum
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at technical conferences. Position Requirements Recent or soon-to-be-completed PhD (typically completed within the last 0-5 years) in mechanical engineering, materials science, civil engineering, computer
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years ) Ph.D. in Engineering, Operations, Computer Science, Mathematics or a related field. Knowledge of optimization, power systems operations and planning, electricity markets, issues surrounding
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of chemical and electrochemical principles to control and improve product morphology, product quality, and process efficiency at engineering scales. With guidance, the appointee will : Develop novel process
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morphology, product quality, and process efficiency at engineering scales. With guidance, the appointee will : Perform experiments with multimodal sensors to advance the technical understanding and application
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”, “Firstname_Lastname_cover_letter”. Include links to code examples in your CV (e.g., GitHub page, past project repositories). Position Requirements A recent PhD (completed within 5 years, or soon to be completed) in computer science
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Qualifications: Ph.D. (completed within the past 0-5 years) in computer science, electrical engineering, applied mathematics, or a related field. Strong proficiency in Python, with additional experience in C, C
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for critical energy and technology sectors. Ability to assess the economic and operational impacts of large-scale AI adoption (e.g., data centers, compute infrastructure) on U.S. electricity demand, generation
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engine modeling code. Perform high-fidelity CFD simulations of turbulent and reacting flows pertaining to gas turbines and detonation engines using spectral element method (SEM). Perform scalability
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operando experiments under electrical, thermal, or mechanical bias to capture real-time defect dynamics. Integrate multimodal datasets and collaborate with AI/ML teams for data fusion, physics-informed model