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postdoc position (with a possible extension for 1 more year) to lead cutting-edge research in remote sensing and deep learning as part of the Ethio-Nature project, a major international research
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with expertise in glaciology and remote sensing for a period of 2 years (24 months) commencing as soon as possible. About the position The project addresses ice-dammed lakes in Greenland and the
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of machine learning, remote sensing and hydrology to evaluate and validate nature-based solutions that enhance local recharge and support the replenishment of shallow groundwater systems in dryland
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genetic drivers of individual variation in woodland phenology across temperate and boreal habitats. This multidisciplinary project combines fieldwork, remote sensing (camera and drone-based imagery), and
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, a large initiative funded by the Danish Ministry of Foreign Affairs and managed by Danida Fellowship Council. Ethio-Nature aims to optimize the use of machine learning and remote sensing to site
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, a large initiative funded by the Danish Ministry of Foreign Affairs and managed by Danida Fellowship Council. Ethio-Nature aims to optimize the use of machine learning and remote sensing to site
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temperate and boreal habitats. This multidisciplinary project combines fieldwork, remote sensing (camera and drone-based imagery), and genetic analysis, aiming to elucidate the adaptive potential of species