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flows, scientific machine learning, optimization, inverse problems, or data assimilation, who have the potential to supervise PhD and master's student research with ability to contribute to curriculum
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 1 month ago
properties, and their vertical distribution on a global scale. This project will focus on developing a strategy to best utilize this data in a global atmospheric data assimilation framework. Activities that
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resolved air-pollutant emissions and exposures from observational data. -Work may include statistical or Bayesian inverse modeling, data assimilation, optimization, uncertainty quantification, numerical
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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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experiments. At the core of the methodology is data assimilation, in which the underlying properties of the interphase (mass, volume, density, porosity and morphology) are treated as a latent state
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Cruz Ocean Modeling and Data Assimilation : https://oceanmodeling.ucsc.edu/ Qualifications Basic qualifications (required at the time the application is submitted) Ph.D. (or equivalent foreign degree) in
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, particularly with proficiency using the Regional Ocean Modeling System (ROMS) and its 4-Dimensional Variational Data Assimilation and nesting capabilities. Demonstrated experience working in a Linux
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, particularly with proficiency using the Regional Ocean Modeling System (ROMS) and its 4-Dimensional Variational Data Assimilation and nesting capabilities. Demonstrated experience working in a Linux
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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