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on these topics. Basic Qualifications Ph.D. in Energy/Environmental/Natural Resource Economics or related Applied Economics discipline with a strong quantitative focus. Experience with quantitative optimization
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restoration of function. The successful applicant will combine computational modeling, engineering optimization, and in vivo experiments to advance understanding and application of electrical block of neural
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activity and people positively impact the world. Like the city we call home, UB is distinguished by a culture of resilient optimism, resourceful thinking and pragmatic dreaming that enables us to reach
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 3 months ago
, and create personal and professional sustainability. We optimize our partnership with the UNC Health System through close collaboration and commitment to service. OUR VISION Our vision is to be
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scattering. Builds and optimizes the nonlinear spectroscopy and scattering setup for multiple interfacial molecular structure measurements. Actively collaborates with interdisciplinary teams on research and
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of decarbonization policy pathways for electric power systems. Desired experience includes optimization and simulation of electric power systems under uncertainty, programming in Python, Julia, and/or MATLAB, and
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Responsibilities Research: - Conduct research in AI reasoning, semantic modeling, and knowledge graph development. - Develop and optimize graph databases for structured knowledge representation. - Apply neural
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sensor networks, robotics, energy, and Smart Cities • Network systems and economics, cooperative control and optimization, game theory • Distributed algorithms for decision making • Machine learning and
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postdoctoral researcher will leverage state-of-the-art protein language models (PLMs) and advanced AI-based structural modeling techniques to design and optimize T and B cell receptors (TCRs and BCRs). The work
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response Demonstrated expertise in process development/optimization for macro-scale deformation in AM Experience with multi-physics simulations on high performance computing (HPC) and maching learning (ML