107 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "U.S" "U.S" "U.S" Postdoctoral positions in United States
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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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salutes our veterans and active military members with careers that leverage the skills and unique experience they gained while serving our country, learn more at BNL | Opportunities for Veterans
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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
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off. To access this tool and learn more about the total value of your benefits, please click on the following link: https://resources.uta.edu/hr/services/records/compensation-tools.php CBC Requirement
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, nutrition lesson) and bi-weekly they will engage in a self-guided culinary session at home (prepare an ethnic, plant-based meal). To learn more visit https://www.aceprogramnyc.com/ . 2) The Double Up Foods
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will continue to build from our learnings. https://pubs.rsc.org/en/content/articlelanding/2025/gc/d5gc01813g https://pubs.rsc.org/en/content/articlehtml/2018/gc/c7gc03747c https://pubs.rsc.org/en/content
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, machine learning, and plant genomics. Our lab seeks to explore and understand the regulatory network of plant genes, their regulation in response to environmental stress at the single-cell level, and the
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Remote Sensing; Machine Learning Models for Predicting Wildfire Spread; Wildfire Risk Assessment Through Multi-Modal Data Integration; Automated Vegetation and Fuel Load Mapping Using Computer Vision; AI
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 1 month ago
to): Develop machine learning algorithms that utilize fire products from geostationary satellites to better represent fire evolution and variability Develop machine learning emulators to represent forward
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management, workflow management, High Performance Computing (HPC), machine learning and Artificial Intelligence to enhance our capabilities in making AI-ready scientific data. As a postdoctoral fellow at ORNL