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Salkehatchie, Union, Lancaster and Sumter enable students to earn associate or bachelor’s degrees through a combination of in-person, online or blended learning. All of our system institutions place strong
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U.S. Department of Energy (DOE) | Washington, District of Columbia | United States | about 13 hours ago
policy, and energy jobs. It provides expertise in workforce development, electricity systems, permitting, buildings and industry, mobility and fuels, energy security, supply chains, and the energy system
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. Demonstrated expertise in using machine learning and optimization frameworks in conjunction with FE simulations to assist with component and/or process design is preferred. Excellent written and oral
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rapidly changing priorities and have ability to quickly learn new skills. Must be detail-oriented, well organized with strong communication skills and ability to work in an interactive team environment
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investigate out-of-equilibrium dynamics in high-dimensional disordered systems (including models relevant to machine learning and optimization) by characterizing the fixed points (metastable states, attractors
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Application Areas of Interest: Cyber-Human-Physical Systems: Human-System Interaction, Human-Centered Planning and Design. Smart, Connected, & Healthy Communities: Smart Integrative Energy Systems, Smart
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community partnerships, gaining hands-on experience in cyber-physical energy systems, resilience analytics, and interdisciplinary solutions to complex societal challenges. NSF award number 2418359 Duties and
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, predictive modeling, machine learning, and causal inference methods. Experience with claims-based or EHR-based phenotyping, variable construction, treatment pattern analyses, healthcare utilization studies
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SPECIFICS Join a Dynamic Team Focused on Foundation AI modeling and Physics-Informed Machine Learning as a Postdoctoral Researcher at The Pennsylvania State University. The Pennsylvania State University is
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public health. In this role, you will develop and evaluate novel AI and machine learning methods using large-scale multimodal datasets, contributing to epidemiology-informed foundation models, predictive