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3rd May 2026 Languages English English English Would you like to explore AI methods for forest mapping? Two PhD scholarships: Remote sensing and AI for improved forest mapping and precision forestry
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geographic information systems, cartography, and remote sensing. Students acquire theoretical and practical knowledge, methodologies, and techniques for solving geographical problems. It encompasses scientific
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skills in remote sensing, AI, ecological modelling, and policy engagement, working across disciplines and continents. The project includes an industrial supervisor to support non-academic training and
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/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 to quantify fire severity and analyze
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its maintenance and safety increasingly depend on data. This PhD project will develop new methods that combine remote sensing, physics-based modelling, and Bayesian machine learning to support risk
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to explore GNSS Reflectometry (GNSS R) as a novel, low cost, low power bistatic remote sensing technique optimized for nanosatellite platforms. GNSS R leverages signals of opportunity from existing
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in refining hydrocarbons. Emerging optical sensing technologies, including quantum gas LiDAR, offer the ability to detect methane concentrations remotely with unprecedented sensitivity and spatial
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to classify biological and fire protection degradation in wooden façades on multi-story buildings by combining remote sensing-based façade inspection with microclimate modelling and performance
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herbivores space use behavior in relation to snow conditions, data is required at cm to m resolution. This PhD project will develop and apply remote sensing methods to advance terrestrial snow monitoring
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programming (R or Python). Advantageous: geostatistics, digital soil mapping, remote sensing, GIS, big data or cloud tools. Proactive working style, strong communication skills, and excellent English. Relevant