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on the development of new methods integrating a variety of data types (remote sensing, geology, geophysics, geochemistry) for geological modelling and advanced exploration targeting of mineral deposits
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atmospheric sciences • Knowledge of cloud or aerosol physics • Experience in algorithm development and satellite remote sensing • Good written and spoken English • Ability to work independently as well as in a
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to make a difference. If this sounds like you, you’ve come to the right place! Responsibilities: Conduct original research on joint communications and radar sensing for spaceborne systems, with a focus on
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? Apply now! Education A PhD degree in Remote Sensing, Geography, Earth Science, Agriculture, Ecohydrology, Biometeorology, Hydrology, or a closely related field Experience and skills Three years
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Job Description Are you a skilled and field-ready researcher with a passion for marine monitoring using many different methods and techniques ranging from diver observations to integrating remote
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research results in high-impact scientific journals. Your profile We are searching for a highly motivated candidate who has A PhD in remote sensing, data science, agriculture, ecosystem modeling or similar
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decision-relevant outputs such as restoration and implementation scenarios. The postdoc will collaborate closely with experts in remote sensing, ecology, environmental science, and engineering while
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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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decision-relevant outputs such as restoration and implementation scenarios. The postdoc will collaborate closely with experts in remote sensing, ecology, environmental science, and engineering while
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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