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seven departments: Materials Mechanics Management & Design, Engineering Structures, Geoscience and Engineering, Geoscience and Remote Sensing, Transport & Planning, Hydraulic Engineering and Water
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Your Job: Remote sensing data from satellites are an extremely valuable information source to improve air quality predictions. They monitor aerosol and trace gases often with global coverage, which
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large, multi-institution, project to advance the remote sensing of freshwater resources. The research will be conducted at the Environmental Remote Sensing Laboratory, under the direction of Dr. Hongxing
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subject: Technology/Forest management/Biology Description: The Department is looking for a PhD student within the area of remote sensing of forest. Using remote sensing the PhD student will develop methods
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Term Period: For 24 months Salary: Full time starting salary (if PhD close to completion) is normally in the range of £34,450 per annum; Full time starting salary (if PhD obtained) is normally in
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are rapidly evolving – ranging from remote sensing and automated sensors to genetic techniques and classical field-based inventories. This PhD project focuses on how biodiversity in forests can be measured
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Remote Sensing; Machine Learning Models for Predicting Wildfire Spread; Wildfire Risk Assessment Through Multi-Modal Data Integration; Automated Vegetation and Fuel Load Mapping Using Computer Vision; AI
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of aerosol characterisation using the synergy between remote sensing and in-situ methodologies. The successful candidate will mainly focus on mineral dust and on the Eastern Mediterranean and Middle East (EMME
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | 29 minutes 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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: Biodiversity is a fundamental prerequisite for the ecological functioning, resilience, and long-term sustainability of forests. At the same time, new methods are rapidly evolving – ranging from remote sensing