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sensing and ecology. The successful candidate should have: Required: A PhD degree with a publication record in peer-reviewed international journals Experience with remote sensing, LiDAR, or GIS applications
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sensing and ecology. The successful candidate should have: Required: A PhD degree with a publication record in peer-reviewed international journals Experience with remote sensing, LiDAR, or GIS applications
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. The successful candidate is expected to bring to UA expertise in areas such as environmental change, hydroinformatics, geographic information systems, remote sensing, urban systems, and human-environment
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on spatial remote sensing and geographic information systems (GIS). The new mathematical models developed as part of the Math-Vive PEPR will serve as a basis for building predictive analysis models and
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recruitment process, can be found at https://accedtp.ac.uk/, in the ‘prospective applicants’ tab. Project overview Are you interested in a PhD working on biodiversity and ecosystem service impacts
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of conducting research in GeoAI/Spatial Data Science (e.g., thesis, dissertation, peer-reviewed publication, research assistant role) Preferred Qualifications: Experience teaching GIS, remote sensing, or digital
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analyzing soil water data. Skills in GIS. Analysis of plant data from ground- and/or remote sensing-based monitoring methods. About us The Department of Crop Production Ecology contributes to solving applied
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of datasets in public data repositories and scientific paper. The Research Data Coordinator will assist with data analyses, providing technical support in remote sensing, GIS, programming and project mentorship
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, computational social science, and/or machine learning applications. Acquisition, processing, and analysis of remote sensing imagery. Proficiency with GIS methods, applications, and visualization. Prior experience
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Qualifications Candidates must have a PhD in Geography or applied GIScience by the start date of the appointment. Successful candidates must have teaching experience in GIS, Cartography, or Remote Sensing as