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Field
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hydrologic connectivity metrics. Furthermore, the qualified candidate must possess advanced skills in geocoding, GIS, raster analysis/processing, and the management of large geospatial datasets. Familiarity
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Strong organizational and time management skills Strong quantitative data analysis skills Experience using administrative child welfare data Experience and skills in GIS Grant-writing experience Additional
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systems for testing devices/products. You will possess the skills required to analyse, interpret and apply information from large data sets and knowledge of geospatial datasets and experience of GIS-based
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or related fields programming experience in Python or extensive experience in another high-level programming language is a prerequisite experience in geospatial data science, remote sensing, GIS, and open
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 1 month 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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learning, computer programming, and some understanding of GIS. Primary Function of Organizational Unit: The Department of Built Environment enrolls over 200 undergraduate and graduate majors. The Department
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knowledge of social surveys and GIS are considered advantageous. To apply, please submit your application at https://careers.purdue.edu and include the following materials: (1) letter of application that
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knowledge of social surveys and GIS are considered advantageous. To apply, please submit your application at https://careers.purdue.edu and include the following materials: (1) letter of application that
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such as GPlates, DAC, GIS for DEM analyses, or related software Some experience in field-based geological methods (e.g., sampling, sediment analysis) or willingness to develop these skills Ability
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acquisition and curation, and model development. Geographic Information Systems (GIS). Knowledge of applications of computer vision to problems in built environment and/or livestock farming. Experience in