183 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "U.S" "U.S" research jobs
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identity, or gender expression. To learn more about diversity at the U: http://diversity.umn.edu Employment Requirements Any offer of employment is contingent upon the successful completion of a background
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 2 months ago
include (but are not limited to): Develop algorithms to characterize aerosol speciation from LIDAR fluorescence signals Develop machine learning emulators to represent forward operators for polarimeter-only
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Organization U.S. Department of Energy (DOE) Reference Code DOE-CMEI-RPP-2025-Fall-MEF-Postgrad How to Apply To apply, click Apply at the bottom of this page. Connect with ORISE on the GO! Download
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National Aeronautics and Space Administration (NASA) | Fields Landing, California | United States | about 2 months ago
Countries can be found at: https://www.nasa.gov/oiir/export-control . Eligibility is currently open to: U.S. Citizens; U.S. Lawful Permanent Residents (LPR); Foreign Nationals eligible for an Exchange Visitor
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a unique opportunity to develop cutting-edge high-performance computing (HPC) that incorporate machine learning/artificial intelligence (ML/AI) techniques into visualizations, enhancing the efficiency
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Sciences Directorate, at Oak Ridge National Laboratory (ORNL). This position presents a unique opportunity to develop cutting-edge high-performance computing (HPC) and machine learning/artificial
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 2 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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decision-making, and join a vibrant AI research community at the University of Texas at Austin, become members of The University of Texas at Austin’s Machine Learning Laboratory (https://ml.utexas.edu
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Organization U.S. Department of Energy (DOE) Reference Code DOE-STP-CEFP-2026 How to Apply Click on Apply below to start your application. Connect with ORISE...on the GO! Download the new ORISE GO
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crane. The successful candidate will build reproducible machine learning pipelines, integrate detections into spatial ecological models, and generate conservation-relevant outputs for regional partners