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Field
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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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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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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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: Python, R, SQL, and ArcGIS; • Excellent knowledge of data science techniques and experience working with the following data formats: tabular, multi-level JSON, GIS, and images; • Excellent written
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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
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, thin sections, and well-logs). Experience with database design, data modeling, and data management systems. Proficiency in programming or scripting languages (e.g., Python, SQL) for data handling and