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understanding of these cold cloud systems. About us At the Division of Geoscience and Remote Sensing , part of the Department of Environmental and Energy Sciences , we conduct research, education, and utilisation
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understanding of these cold cloud systems. About us At the Division of Geoscience and Remote Sensing , part of the Department of Environmental and Energy Sciences , we conduct research, education, and utilisation
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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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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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remote sensing data analysis and geographic information systems. Experience in machine learning motivated algorithms and quantitative data analysis. Strong writing and communication skills. What You Need
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evaluation of advanced applications for network benchmarking, road hazard warning, and pseudo-remote driving supported by computer vision, while also supporting the broader research and integration activities
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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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., Teodoro, P. E., ... & da Silva Junior, C. A. (2023). Nutritional monitoring of boron in Eucalyptus spp. in the Brazilian cerrado by multispectral bands of the MSI sensor (Sentinel-2). Remote Sensing
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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | 36 minutes ago
inventories) with satellite remote sensing data (e.g., spaceborne lidar and/or hyperspectral observations) and apply machine learning and deep learning approaches to address these questions. This position is
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advancing your own research and lecturing/supervision skills? If so, we invite you to read on! The Geo-information Science team within the Laboratory of Geo-information Science and Remote Sensing (GRS) is an