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Field
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The Cambridge Sustainable Design Group within the Department of Architecture invites applications for the role of Research Assistant/Associate in Thermal Infrared Remote Sensing for Decarbonisation
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of Sentinel-2 fluvial scenes’. Earth Surf. Process. Landforms, 45, 3120–3140. Carbonneau et al 2020) ‘Adopting deep learning methods for airborne RGB fluvial scene classification’. Remote Sensing of Environment
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two PhD student positions to carry out research with the Signal Processing group in the area of next generation space-terrestrial wireless communications and sensing. We are looking for ambitious and
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Researcher will influence the direction of application areas and algorithm development, receiving direct training in InSAR processing, geospatial data science, and agricultural remote sensing. Co-supervision
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interest, narrowing the scope to natural or cultural sites, and integrating diverse remote sensing datasets. The supervisory team offers interdisciplinary expertise in geospatial analysis, machine learning
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positions to carry out research with the Signal Processing group in the area of next generation space-terrestrial wireless communications and sensing. We are looking for ambitious and creative candidates with
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remote sensing, numerical modelling, and fieldwork. We recognize that no candidate will have experience in all of these areas, and we encourage you to apply if you have the following qualifications
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. This PhD project will investigate the interactions between wildfire disturbance and thermokarst dynamics across Siberia and other Arctic regions using multi-sensor satellite remote sensing data provided by
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evaluating temporal changes in A. longifolia populations and for assessing the impact of biological control agents. The work will comprise the application of remote-sensing and geospatial analysis
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-driven simulations, optical remote sensing and biogeochemical modeling to predict seagrass distribution under various climate and nutrient scenarios. SEAGUARD aims to provide science-based recommendations