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software that allow time-evolving models of complex systems to be calibrated against sparse, indirect, and uncertain observations. The group develops and maintains an open-source Python framework
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-assisted model calibration, or pattern detection in large observational datasets) to improve nutrient-cycling representation and reduce predictive uncertainty in models. Collaborate with an interdisciplinary
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-assisted model calibration, or pattern detection in large observational datasets) to improve nutrient-cycling representation and reduce predictive uncertainty in models. Collaborate with an interdisciplinary
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illumination effects. Coordinate optical measurements with the imaging teams; provide calibrated data, metadata, and analysis to ORNL and university collaborators. Develop instrument-control and data-analysis
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simulations in fusion devices. Support coordinated multi-physics simulations of fission reactor core, fusion device blankets, and other system components. Develop reduced-order calibration approaches and apply
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calibration, coordinate-frame management, timestamp synchronization, and data acquisition across heterogeneous devices. Develop and evaluate multi-sensor localization and state-estimation methods that fuse
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analyzing and interpreting experimental data to drive product innovation, as well as obtaining and calibrating simulation parameters based on laboratory results. Regular interfacing between experimental and
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analysis by integrating diverse datasets (e.g., in situ observations, remote sensing products, model simulations) to inform model development, calibration, and validation. Collaborate with a
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, calibration, and application. Experience with computational methods including steady-state modeling, dynamic simulation, computational fluid dynamics (CFD) to support system design and performance optimization