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in statistical programming (R, Python, Julia, MATLAB). Familiarity with GIS and spatial analysis tools (ArcGIS, QGIS, or R spatial packages). Ability to integrate multidisciplinary datasets
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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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