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the design and operation of next-generation thermal systems, developing strategies to model, optimize, predict, and autonomously control thermal systems behavior in complex systems. The candidate will
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transport models to assess the production and transport of in-vessel impurities in MPEX operating scenarios. Perform predictive modeling to inform the design of new MPEX target geometries, with a focus to
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Landscape analysis and modeling, with a focus on training and application of predictive machine learning tools. This researcher will synthesize regional-scale remote sensing imagery and ecological monitoring
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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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system models and quantifying uncertainty in their predictions. Conduct fundamental research on the formulation of probabilistic system dynamics models, including knowledge integration, likelihood
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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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data-model integration, leveraging the U.S. Department of Energy’s (DOE) Leadership-Class Computing Facilities to advance predictive understanding of complex environmental systems. Major Duties
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) project, an interdisciplinary and multi-institutional collaboration focused on disturbance-driven ecosystem transitions and their impacts across the U.S. Gulf Coast. EGRET employs an integrated model
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of large-scale geospatial and time-series datasets. The candidate will develop and evaluate multimodal AI models to characterize vegetation and land-surface dynamics and quantify ecosystem responses and
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predictive modeling Design and implement reproducible pipelines for data acquisition, feature engineering, model training, evaluation, packaging, and deployment Help the group envision, design, develop, test