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Field
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requirements: The candidate must have obtained their PhD within the last 7 (seven) years, counted from the start date of the fellowship, and have experience in remote sensing applied to agriculture and/or
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National Aeronautics and Space Administration (NASA) | Huntsville, Alabama | United States | about 3 hours 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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use their skill for the benefit of society in the long term. Is Your profile described below? Are you our future colleague? Apply now! Education PhD degree in remote sensing, preferably with a doctoral
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the long term. Is Your profile described below? Are you our future colleague? Apply now! Education PhD degree in remote sensing, preferably with a doctoral thesis on RTM inversion or deep learning in remote
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Join and help us to derive global forest biomass data from the European Space Agency’s Biomass satellite mission. If you have interests in remote sensing, machine learning and forests, this is the
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | 2 months ago
. Description: New techniques and instrumentation are developed and applied for remote atmospheric measurements. Current research includes cloud and aerosol studies using space-based lidars such as the Cloud
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Researcher position to join the DISECO project (The role of disequilibrium on niche and biodiversity effects over ecosystem trajectories). The position focuses on the remote sensing component of the project
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their strategies. Do you want to know more about LIST? Check our website: https://www.list.lu/ How will you contribute? You will be part of LIST’s Remote sensing and natural resources modelling group Embedded in
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Join us at the Department of Electrical and Computer Engineering at Aarhus University for a postdoctoral position focused on deep learning based analysis of remote sensing data for groundwater
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postdoctoral research project. The project focuses on the development and application of a remote sensing algorithm for monitoring the physicochemical properties of aerosols based on optical measurements taken