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, and access world-leading research computing facilities—all while working on problems of genuine national significance. We seek outstanding candidates with broad knowledge of hydrology and water
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knowledge of models of strongly correlated electron systems. Proficiency with scripting or programmatic languages, such as Python, c, and MATLAB. Excellent written and oral communication skills. Motivated
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more than 60 years of achievement in local, regional, national, and international environmental research. Our vision is to expand scientific knowledge and develop innovative strategies and technologies
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physics-informed and physics-ML hybrid approaches that integrate domain knowledge with data-driven methods to advance hydrological process understanding and prediction. Conduct multimodal, multiscale data
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Laboratory focuses on artificial intelligence and computational research and applies this knowledge to support the nation’s leading initiatives. We hire top researchers who are ready to tackle the hardest
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, or graph-based encodings in materials and molecular AI. Familiarity with frameworks for automated and reproducible workflows. Knowledge of governing regulations around privacy (e.g., HIPAA, ITAR), including
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Programming experience in scientific computing environments Preferred Qualifications: Experience developing Finite Element Method or CFD models for composite manufacturing applications Knowledge of machine
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environmental science, environmental chemistry, civil/environmental engineering, biogeochemistry, biology or related discipline. Knowledge and experience in laboratory environment. Ability to articulate a
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in ORNL’s Center for Radiation Protection Knowledge (CRPK). The candidate will work with experts in computational radiation dosimetry and risk assessment. The candidate should be an independent thinker
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environments. Knowledge of materials behavior in extreme environments (e.g., high temperature, irradiation, corrosion, and mechanical stress) and familiarity with multiscale and continuum modeling approaches