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Field
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geoscience and remote sensing methods with AI and advanced computing technologies for Earth observation (EO) applications, including climate science, forestry, or agriculture. Your doctoral research will
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scales using hyperspectral earth observation data. Within the ASCENT project, you will work as a PhD candidate in an interdisciplinary consortium with remote sensers, ecologists, data scientists, and
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allowance of £21,805. Research funds are available for the field and lab related aspects of the PhD research. Overview Agricultural expansion and intensification are major drivers of habitat fragmentation and
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. The combined observation of soil processes with plant functional traits and structure of vegetation captured by remote sensing (e.g. LiDAR, multi- and hyper-spectral imagery) in experiments and at contrasting
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for admission. The project would suit a candidate with a background in surveying/geodesy, geomatics, remote sensing, geospatial science, civil/environmental engineering, hydrology, Earth observation
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heterogeneous sources of information—including remote sensing, forest inventory data, existing forest maps, environmental and climatic data, and emerging large-scale AI representations—can be jointly exploited
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Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 24 Sep 2026 - 23:59 (Europe/Andorra) Country Spain Type of Contract Temporary Job Status Full-time Hours Per Week
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Award Summary 100% Home fees covered and a minimum tax-free annual living allowance of £21,805. Research funds are available for the field and lab related aspects of the PhD research. Overview
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includes agronomic field studies, crop modelling and the use of remote sensing and spectral techniques for crop monitoring. The research environment includes expertise in forage production, crop ecology
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buildings. The PhD project focuses on the development of novel applications for the use of earth observation data in transportation infrastructure monitoring. The research covers various modes of transport