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Posting Details Position Details Title Postdoctoral Fellow - AI-Enabled Immune Digital Twin Workflows, Data Assimilation, and Ensemble Updating Appointment Status Non-Tenure Track Department IU
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assimilation (DA) framework. The project aims to estimate the state of dynamical systems from sparse observational time series, combining data-driven approaches with high-fidelity and/or reduced-order
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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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ensemble weather forecasting, deep learning for spatiotemporal data, uncertainty quantification, data assimilation, or related areas. Develop and rigorously evaluate AI-based weather forecasting
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research in probabilistic and ensemble weather forecasting, deep learning for spatiotemporal data, uncertainty quantification, data assimilation, or related areas. Develop and rigorously evaluate AI-based
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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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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | about 4 hours ago
operational environmental datasets. Evaluate model performance through validation and comparison with available measurements, assess uncertainty and limitations, and support data assimilation
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operational environmental datasets. Evaluate model performance through validation and comparison with available measurements, assess uncertainty and limitations, and support data assimilation
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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