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Organization U.S. Department of Defense (DOD) Reference Code ERDC-CHL-2025-0011 How to Apply Click on Apply now to start your application. Application Deadline 8/31/2025 3:00:00 PM Eastern Time Zone Description The U.S. Army Engineer Research and Development Center's Coastal & Hydraulics...
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Fellow in Remote Sensing and Geospatial Intelligence There is a vacancy for a PhD Research Fellow in remote sensing and geospatial intelligence at the Department of Earth Science and the Bjerknes Centre
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1st October 2025 Languages English English Norsk Nynorsk English PhD Research Fellow in Remote Sensing and Geospatial Intelligence Apply for this job See advertisement UiB - Knowledge that shapes
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Job Description Job Alerts Link Apply now Job Title: Research Fellow (Vegetation Remote Sensing) Posting Start Date: 17/07/2025 Job Description: About The Department of Geography at the National
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Primary Purpose: To lead remote sensing research that quantifies the impacts of beaver foraging on vegetation structure and aboveground carbon stocks in montane peatlands, and to generate new
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systems that fuse multi-modal remote sensing, soil and phenology data to enable crop classification and precise, customized fertilizer recommendations. Selection criteria (short) Required PhD (awarded
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to Singapore’s strategic priorities in space science and remote sensing. Key Responsibilities: Lead and execute the research project with minimal oversight, from hypothesis formulation to publication. Design and
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on rapid and accurate quantification of disasters using remote sensing and space geodesy. They will also advance InSAR processing algorithms to optimise change detection capability in Southeast Asia, where
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security goal in Africa, with a special focus on developing methods/tools that use multi-source remotely sensed data. The research aims to improve our understanding of the integrated functioning
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–policy interface for municipal biodiversity conservation and climate adaptation with nature-based solutions Processing and evaluation of remote sensing data, including methods of computer vision