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Field
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | 3 months ago
retrieval algorithm development with focus on using the polarimetric signals, the new FIR or sub-mm bands, and/or the ML/AI approach; (3) ML/AI application on system/pattern tracking on satellite images
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, curate, and analyze field measurement datasets and associated environmental and economic information for model parameterization and validation. Develop or enhance model algorithms simulating carbon and
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artifacts, and developing an independent research agenda in AI for science. Core responsibilities include: Leading research on foundation models, including problem formulation, algorithmic development, and
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National Aeronautics and Space Administration (NASA) | Hampton, Virginia | United States | 3 months ago
questions in Earth System science is also a goal of this opportunity. Efforts are expected to be conducted in collaboration with the SAGE algorithm/data processing and validation teams, as
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involves conducting data analysis, implementing machine-learning algorithms to achieve or exceed industry-standard bits-per-second (BPS) accuracy, and preparing results for publication in peer-reviewed
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | 3 months ago
of radiance data from new hyperspectral infrared instruments such as IASI-NG, MTG-IRS Enhancement of CrIS radiance assimilation algorithm are highly encouraged. - Use machine learning methods to cope with model
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | 3 months ago
Lidar and the Roscoe upper troposphere/lower stratosphere lidar). Additional projects include the development of machine learning and advanced data processing algorithms, and participation in upcoming
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-guided) Evolutionary trajectory analysis and fitness landscape modeling Integration of predictive algorithms with experimental iteration cycles High-throughput screening and selection platform development
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of quantum algorithms for hybrid quantum simulators. Applicants should have a PhD in Physics, Chemistry, Computer Science, or a closely related field. To apply, a CV, a brief statement of research interests
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High-Energy Physics (HEP). We seek highly qualified candidates with interest and experience in ML algorithms including unsupervised techniques, time-series modeling, and clustering algorithms