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Field
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Developer, and GIS Data Specialists to streamline workflows, enhance data quality, and drive efficiency in a fast-paced, cloud-centric environment. The position reports to the data products leader. What We Do
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the developed geospatial databases to evaluate trends in stream networks across the US. Work will be done primarily in python and GIS. Candidates will be expected to create maps and graphs of trends in network
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synthesis, (b) numerical and analytical modeling environments (e.g. Python), (c) geoprocessing and GIS analytics, and (d) data-driven model development. Demonstrated ability to meet deadlines and effectively
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tools from remote sensing, Geographic Information Science (GIS), graph theory, and data science to address complex research questions. Analyzes both aspatial (e.g., tabular) and spatial (vector and raster
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on individual assessment. Special weight will be given to: Documented experience in analysing ecological or biological data using Python or R. Basic knowledge of database management (e.g., SQL), data retrieval
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limited to: Conducting statistical analysis of PFAS in groundwater data. Performing spatial data analysis using orbital or airborne images and GIS tools. Reviewing and compiling relevant literature
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modeling tools, especially in Python (e.g., EPANET, Water Network Tool for Resilience - WNTR, EPA SWMM, pipedream). Knowledge of geographic information systems (GIS) data and analysis for water
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GIS course focused on emerging technologies and analytical techniques in geospatial science. This course will incorporate cutting-edge tools such as Python for GIS, machine learning for remote sensing
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degree or a good honours degree in Remote Sensing, Geomatics, GIS, Computer Science, Photogrammetry or a related field with three or more years of research / relevant work experience. Applicants
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”. Qualifications Applicants should: (a) have a PhD degree in Remote Sensing, Geomatics, GIS, Computer Science, Photogrammetry or a related field, and must have no more than five years of post-qualification