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synthetic data generation, simulation platforms (e.g., Unreal Engine, Omniverse), or virtual/augmented reality Knowledge of scientific domains such as engineering systems, physics-based modeling, or quantum
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Requisition Id 16010 Overview: The Watershed Systems Modeling Group (WSMG) within the Environmental Sciences Division (ESD) at Oak Ridge National Laboratory (ORNL) is seeking a highly motivated
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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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, 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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performance modeling, static analysis, or PIM/heterogeneous architecture research. Knowledge of large-scale scientific computing applications and algorithms (sparse linear system solvers, dense matrix
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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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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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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
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a particular emphasis on error-corrected methods for future fault-tolerant quantum computing. The algorithms will be designed to address key models of quantum materials, such as the Hubbard model
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the last 5 years Preferred Qualifications: Strong background in experimental systems related to heat and mass transfer systems. Knowledge of CFD tools and analytical modelling is preferred. Experience with