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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 13 hours ago
observations and model-based data. Apply machine learning techniques to optimize factor weightings and reveal critical wildfire drivers. Validate models using multi-source wildfire data (MODIS, VIIRS, and NOAA
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models that examine how brain and behavioral networks give rise to mental health disorders. This interdisciplinary research integrates approaches from network science, machine learning, and developmental
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, Robotics, Computer Vision, or related disciplines. Proven expertise and hands-on experience in one or more of the following areas: large language models (LLMs), end-to-end learning, AV localization
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and great opportunity of interdisciplinary training in machine learning and functional genomics. The project combines cutting-edge computational approaches, especially state-of-the-art machine learning
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Qualifications Minimum Education and Experience A doctoral degree in Industrial Engineering or a related field is required. Strong and demonstrated experience in data science and machine learning for large-scale
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longitudinal modeling, machine learning methods, subgroup analysis, or other advanced modeling techniques is highly desirable. Software Proficiency: Experience with neuroimaging tools such as AFNI, SPM, FSL
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on an optical table and integrating novel optics to microscopy are a requirement for this position. Knowledge in computational imaging, mathematical modeling, strong computer programming skills in MATLAB and/or
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are encouraged to Be Curious about opportunities for learning, creating, discovering, and innovating, and are encouraged to learn from failure. Show Your Fire by joining our team and exhibiting your passion and
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learning, deep learning, and large language models (LLMs), for the analysis of high-throughput multi-omics datasets (especially single-cell and spatial omics) and large textual corpora (e.g., scientific
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. Position Description The Electron-Ion Collider (EIC) Directorate has an opening for a Postdoctoral Research Associate to support the development and implementation of radiation transport modeling and machine