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Field
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close collaboration with a specific group (DARSA) specialized in developing and applying remote-sensing tools and innovative open-source machine-learning methods. Key responsibilities Develop effective
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rolling basis with start dates as early as 1/1/2026 and as late as 3/1/2026. Group or Departmental Website: https://simpsoba.su.domains/ (link is external) How to Submit Application Materials: Please upload
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 1 month ago
consider one or multiple subtopics that our group is particular interested in and invests on: (1) ice microphysics remote sensing from infrared to microwave spectra (TIR, FIR, sub-mm, MW); (2) cloud
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to critical infrastructure, you authorize the University to conduct routine background checks. Essential Duties and Responsibilities The incumbent will be working in the areas of remote sensing, improving
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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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in their decisions and businesses in their strategies. Do you want to know more about LIST? Check our website: https://www.list.lu/ How will you contribute? We are seeking a highly motivated
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-impact journals and present research at international conferences. Your Profile Requirements: Education: PhD in Remote Sensing, Environmental Engineering, Geoinformatics, Telecommunications, or a related
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 6 hours ago
2) I-485 or I-589 forms in pending status Questions about this opportunity? Please email npp@orau.org Qualifications Desired Qualifications We seek a motivated researcher with a PhD in remote sensing
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on remote sensing of air quality. Emphasis will be placed on using satellite observations to understand the impacts of wildfires and prescribed burning on air quality. The candidatemust have a Ph.D. in a
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water quality parameters and predict cyanobacteria blooms in the Tietê system reservoirs. Activities: 1. Develop machine learning models for estimating water quality parameters via remote sensing; 2