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Experience with satellite remote sensing and geographic data Excellent English communication skills (spoken and written) Highly desirable skills: Experience in GIS, remote sensing, statistical analysis and
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Requirements The ideal candidate should have: A PhD in soil remote sensing, plant-soil interactions, near-surface geology, or a related discipline. Experience in field-based soil and environmental research
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environmental data. Proficiency in Python, SQL, and Jupyter Notebooks. Experience with LiDAR data processing and remote sensing. Experience with environmental modeling, downscaling, and data integration
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the broader research community. Experience and Qualifications PhD in Soil Science, Remote Sensing, Environmental Science or a related field. Strong experience in Soil sciences (e.g., physics, chemistry
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Charles Henry Turner Post-doctoral Fellow, Department of Geography & GIS, College of Arts & Sciences
description can be changed at any time. Minimum Requirements Minimum qualifications for the Turner post-doc fellow include the following: PhD by the hire date in Geography, Remote Sensing, Earth Sciences, or in
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in collaborative research environments. Interest in mentoring students and contributing to educational initiatives. Experience with remote sensing, GIS tools, and image analysis techniques is an
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for Remote Sensing Application (CRSA) is a transversal structure across several UM6P Programs. Research within CRSA is organized around several major areas that aim to ensure the challenging Food and Water
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, multi- layered spatial data sets (e.g. Remote Sensing and GIS), and contributing to the growth of the interdisciplinary Integrated Coastal Studies Program, which focuses on issues related
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. PhD degree in Hydrology, Environmental Science, Civil Engineering, or a related field. Experience with hydrological models (e.g., SWMM, HEC-RAS, Delft-FEWS, CityCAT). Proficiency in GIS tools, remote
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students and contributing to educational initiatives. Experience with remote sensing, GIS tools, and image analysis techniques is an advantage, as is knowledge of genetic methods (e.g., SNP-based data