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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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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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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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hydrologic, geologic, and water quality data using tools such as GIS, statistical software, and data visualization programs. Coordinates with investigators and staff of other University departments and
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. Utilizing GIS tools to create map visualizations of the data across different spatial scales and temporal ranges. You are a Bachelor or Master student, enrolled at a German university, and ideally meet the
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representations of GIS data, using GIS hardware and/or software applications, related to workforce and economic development. Ability to analyze data related to local economic development, including identifying
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Data tools including Cloud, Hadoop, Pig, Hive and Spark; GIS tools and systems; querying data from relational databases using SQL; R or Python; experience developing courses or professional education in
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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
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grants for future research in the field of spatial history. Qualifications Required: Strong background in information science, library science, digital humanities, or GIS. Experience managing and
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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