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Scholar in physical oceanography focused on numerical ocean modeling, ocean data assimilation, and computational methods for understanding and predicting regional and coastal ocean circulation. This is
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two phases of burning: flaming and smoldering. This project will focus on utilizing these fire products in a global atmospheric data assimilation framework. Activities that would be involved in this
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 1 month ago
two phases of burning: flaming and smoldering. This project will focus on utilizing these fire products in a global atmospheric data assimilation framework. Activities that would be involved in this
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and application of the AgroC agroecosystem model for simulating water, carbon, nutrient and energy fluxes at the field and farm scale Integration of AgroC with the Parallel Data Assimilation Framework
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learning-assisted methods: data assimilation, uncertainty quantification (UQ), and machine-learning-based moment closure models. · Multiscale modeling: kinetic limits of many-particle dynamical systems
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equations: fast algorithms with stability/convergence analysis • Data-driven and machine learning-assisted methods: data assimilation, uncertainty quantification (UQ), and machine-learning-based
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chemistry; climate and atmosphere-ocean dynamics; cloud microphysics, severe storms, and mesoscale meteorology; data assimilation, machine learning, and causal discovery; education and human resources
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chemistry; climate and atmosphere-ocean dynamics; cloud microphysics, severe storms, and mesoscale meteorology; data assimilation, machine learning, and causal discovery; education and human resources
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. Competencies: Expertise in uncertainty quantification and statistical methods. Experience with data assimilation techniques. Experience applying machine learning approaches to ocean or coastal modeling
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candidate will develop and apply cutting-edge remote sensing or photogrammetry methods, in combination with data science approaches such as machine learning and data assimilation via cryospheric models