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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 months ago
expertise in children’s environmental health, the built environment, disaster epidemiology, pesticide exposure, endocrine disruptors, air pollution, PFAS exposures, and GIS, as well as other areas. Training
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expected to have experience in hydrologic/hydraulic modeling and in one or more of the following topics: in situ sensor installation and flood monitoring, GIS & geospatial big data, AI/ML and data science
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and optimizing the SNI by integrating clinical, economic, and social vulnerability data within a Geographic Information System (GIS)framework. This will involve conducting rigorous quantitative and
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following software programs (e.g., R, Stata, Python, GIS); Have strong organizational and communication skills. Preferred Qualifications Experience with survey design and impact evaluations in emerging
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at the time of application is accepted, but Ph.D. is required by the start date. • Candidate must have experience using GIS and remote sensing software and satellite data products in analyzing glacial lakes
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information, remote sensing data, and GIS software. Experience in deep learning and computer vision. Experience in developing software tools and products. Experience in writing scientific papers and successful
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to participate in fieldwork. Experience with a range of statistical methods and spatial analysis tools including GIS or a related software (such as Q-GIS). Preferred Qualifications Experience driving small boats
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governmental GIS expertise also available. The Postdoctoral Fellow is a full-time temporary position and the candidate can begin as early as October 2024. The Fellowship will last one year, with the strong
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 7 hours ago
/medicine/gi/education/basic-science-track/ Minimum Education and Experience Requirements PhD, MD, MD/PhD or DVM or equivalent degree in related fields. Required Qualifications, Competencies, and Experience
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: Preferences: Methodological expertise with multilevel, longitudinal data analysis, and GIS mapping. The research project will address issues related to confounding and effect modification. Additional