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Join the M-WAVE team to develop a forward operator for land data assimilation. Job description Challenge: Understanding the climatic drivers of crop failure, monitoring crop growth and implementing
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 1 month ago
. Description: This opportunity is closed to applicants who are Senior Fellows (5-years or more past PhD). The Goddard Earth Observing System (GEOS), developed by NASA’s Global Modeling and Assimilation Office
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 1 month ago
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 would be involved in this project
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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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, ocean data assimilation, and computational methods for understanding and predicting regional and coastal ocean circulation. This is a full-time position for 2 years, with the possibility of a 3rd year
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organization. About the position The Nansen Centre has long expertise in data assimilation (DA) and climate predictions, initially introducing the Ensemble Kalman Filter (EnKF) data assimilation method in
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of the Laboratory for Conservation and Science and the Head of Conservation at LCSD to foster understanding and assimilation of results and approaches of scientific research in the arts among curators, conservators
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as a member of the GHER contributing to the EU research project COMEDI in a consortium of 11 leading partners in the field of data assimilation and deep learning. A successful applicant will develop
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of atmospheric dynamics, process scale models, and numerical computation techniques Knowledge of data analysis Knowledge of using atmospheric and hydrological observational datasets, data assimilation techniques
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performance through validation and comparison with available measurements, assess uncertainty and limitations, and support data assimilation, initialization, forcing, downscaling, or model-selection activities