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of the following models, software/programming languages will be preferred: a. Extreme value analysis b. Land surface modeling and/or remote sensing; Water resources management; Crop modeling c. Data analysis tools
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 25 days ago
Assistant – GIS Analyst with GIS or remote sensing background knowledge who will be using programming and GIS software to assist with a range of tasks, from automated spatial data collection, geospatial data
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in the context of global sustainability standards. Key Responsibilities: Research and Development: Conduct cutting-edge research that utilizes GIS, remote sensing, and other spatial technologies
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staff position within a Research Infrastructure? No Offer Description The project aims to apply artificial intelligence (AI) to map agricultural plastic in remote sensing images. The fellow will work
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environmental land use (peatland ecosystems) data sets. Experience of using Geographical Information Systems (ArcGIS or open GIS such as QGIS), remote sensing, use of satellite data, drone or aerial surveys
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Qualifications Knowledge of Remote sensing of surface water quality, numerical modeling, GIS, leadership and advising skills, teaching, & writing experience. Appointment Type Salary Information $50,000-$55,000
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loss data. Computing skills including experience in advanced statistic programming languages (R and/or Python), remote sensing and GIS software (Google Earth Engine, ArcGIS and/or QGIS). Demonstrated
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of GIS, remote sensing, and other analytical software tools. Excellent analytical, organizational, and problem-solving skills. Strong publication record in relevant academic journals. Excellent
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Education (MOE) aims to improve the measurement forest structure and aboveground biomass by linking these remote sensing observations to ground measurements of representative ecosystems in Southeast Asia
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stakeholders. The candidate will help to support and grow the geographical (i.e., GIS, remote sensing, GPS, UAVs) and eco-geological (i.e., salt marsh/mangrove/estuarine processes) monitoring capabilities within