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/Responsibilities: Develop and apply AI foundation models for hydrological and Earth system modeling, with emphasis on improving predictive capabilities for compound flooding in coastal regions. Design and implement
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behavior, and materials performance under irradiation, thermal, and mechanical loading. Plan and perform thermophysical property measurements and integrate measurement results with modeling predictions
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properties. Experience operating and maintaining Quantum Design instruments. Familiarity with the health and safety hazards associated with an experimental condensed matter laboratory that houses an extensive
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team of scientists to develop in situ monitoring technologies for DED-based AM processes. Design, integrate, and deploy multi modal sensor systems (including but not limited to optical, thermal, acoustic
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and carbonation reactions in aqueous solutions, amorphous materials and at mineral-water interfaces. Collaborate with ORNL researchers on the design and execution of experiments to measure
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, work together, and measure success. Basic Qualifications: A PhD degree in Meteorology, Atmospheric Science, or a related discipline. A minimum of 1 year of experience with the Weather Research and
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, the Frontier supercomputer, and collaborate with experts in machine learning, optimization, electric grid analytics, and image science. The successful candidate will design and implement differential privacy
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uncertainty quantification. The position comes with a travel allowance and access to advanced computing resources. The MMD group is responsible for the design and development of numerical algorithms and
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engineering, or related fields completed within the last five years. Quantitative and analytical research background applicable to advanced manufacturing technologies and manufacturing systems Experience with
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, objective, and publicly available geothermal well life cycle assessment analysis. This project will conduct research into alternative geothermal well designs that can improve the life cycle value