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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | 18 days ago
. Description: This research opportunity focuses on ground-based remote sensing of atmospheric composition using high-resolution UV-visible-near infrared spectroscopy at JPL’s Table Mountain Facility (TMF
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National Aeronautics and Space Administration (NASA) | Huntsville, Alabama | United States | 18 days ago
to advance use of foundation models for Earth Science research and applications, including fine-tuning experiments Use of remote sensing, models, and/or machine learning to further our understanding
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. The successful candidate will play a key role in designing and implementing research at the intersection of sensor data collection, machine learning, remote sensing, and real-time agricultural decision-making
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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 17 hours ago
; experience working with a range of observational data sets of atmospheric composition such as ground based and remote sensing measurements; and an emerging strong track record of scientific output
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Landscape analysis and modeling, with a focus on training and application of predictive machine learning tools. This researcher will synthesize regional-scale remote sensing imagery and ecological monitoring
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systems. Spectroscopy, hyperspectral imaging, remote sensing, IoT, and process measurements are important data sources within this broader framework rather than requirements defining a single experimental
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(ORNL) is seeking a highly motivated Postdoctoral Researcher with expertise in artificial intelligence and machine learning (AI/ML), remote sensing, Earth and environmental sciences, and the analysis
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | 18 days ago
research opportunity invites a participant to investigate that coupling in both directions in support of NASA's microwave remote sensing missions. In the forward direction, physically based inversion of soil
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to the development of remote sensing algorithms, simulation and modeling capabilities, and artificial intelligence/machine learning (AI/ML) methods in support of the goals of the joint NASA/USGS Landsat mission
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are particularly relevant. The developed numerical models will leverage a large suite of in-situ and remotely sensed observational datasets, spanning from subsurface to atmosphere. You will have experience