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project deliverables are met. Any other ad-hoc duties assigned by Supervisor. Job Requirements PhD in Geography, GIS, Remote Sensing, Environmental Science, Earth Science, or related disciplines. Strong
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, retrieval models informed by routinely available remote sensing data in the visible-near infrared spectrum, or more complex land surface models which assimilate those data. However, biophysical variables
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | 28 days 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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for remote sensing and uncertainty estimation. Candidates must have a strong programming background. Requirements: PhD in Computer Science or a related field with a strong emphasis on machine learning
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Scholarship (BIPD) to holders of a PhD degree obtained in less than 3 years within the scope of the project 3D-FIRST-“Enhanced Forest Inventory Metrics through Advanced Remote Sensing Technologies”, taking
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due time of three years Successful candidates will work together with an experienced PhD researcher at the Institute of Photogrammetry and Remote Sensing and together with other chairs being part of
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of Virginia aims to improve understanding of climate-related hazards (wildfire, drought, flood) and their impacts on natural environments and human communities using remote sensing, Earth system modeling, and
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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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interdisciplinary environment, with close links across ecology, biodiversity, AI, and remote sensing — both within Aarhus University and with leading collaborators worldwide. A stimulating research culture that
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remote sensing, geodesy and geodynamics, environmental monitoring, geo-hazards studies, intelligent transport systems, smart city, utility system management, location-based services, geographical social