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to design and implement experiments, perform data analyses, and interpret experimental results. Excellent interpersonal, oral, and written communication skills. Preferred Qualifications: Demonstrated
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for geothermal casing related harsh environments applications. A background in polymer chemistry research or related fields, composite material development, material science, and data analysis is preferred. Strong
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participation, and dissemination of research results. Adhere to requirements for protecting proprietary or sensitive information and follow ORNL cybersecurity policies and guidelines. Basic Qualifications: Ph.D
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in the areas of Hydrological and Earth System Modeling and Artificial Intelligence (AI). The successful candidate will have a strong background in computational science, data analysis, and process
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strengths in high-performance computing, system architecture, and data analytics with applications in a large variety of science domains. NCCS is home to some of the fastest supercomputers and storage systems
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science and analytics at scale to enable scientific discovery across the physical sciences, engineered systems, and biomedicine and health. It provides foundations and advances in quantum information
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evolution, phase stress, and defect evolution using advanced data analysis tools. Perform alloy fabrication and processing (e.g., arc melting, heat treatment) and relate processing to performance. Apply
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modeling, optimal power flow (OPF), surrogate modeling, and data-driven analysis of large-scale electric power system simulations on DOE leadership-class computing resources. The candidate is expected
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analysis and technoeconomic analysis without significant direction from ORNL staff Leverage primary equipment data from both within ORNL and from industrial partners from across the U.S. to quantify costs
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chemistry, specifically x-ray photoelectron spectroscopy. Electrochemistry background, specifically time-resolved impedance. Candidates must show proficiency in developing techniques and data. An excellent