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Proficiency: Proficiency in Geographic Information Systems (GIS) to map and analyze spatial determinants of urban health. Predictive Modeling Skills: Ability to develop predictive models and simulation tools
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devices into complex digital systems. Advanced expertise in machine learning and artificial intelligence for predictive and prescriptive urban data analysis. Experience in visualizing and analyzing spatial
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assessment in urban environments. Proficiency in hydrological modeling software (SWMM, HEC-RAS, or equivalent). Experience with GIS tools (ArcGIS, QGIS) for spatial analysis and mapping of water flows and risk
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The successful candidate will: Characterize the spatial and temporal variability of soil salinity by integrating very-highresolution remote and proximal sensing approaches (e.g., near-surface sensing, UAV-based
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hydro-climate studies. Strong background with GIS tools and spatial analysis techniques. Demonstrated expertise in climate variability assessment and the use of climate models. Experience with
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work with researchers and students involved in spatial hydrology. Publish scientific papers in peer-reviewed journals and deliver presentations and progress reports. Contribute to the supervision
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) technologies for collecting data on environmental and health parameters (air quality, noise, mobility). • GIS Proficiency: Proficiency in Geographic Information Systems (GIS) to map and analyze spatial
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artificial intelligence for predictive and prescriptive urban data analysis. • Experience in visualizing and analyzing spatial and functional interactions within urban infrastructure. Personal and
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techniques. Proficiency in R, Python, or MATLAB for data processing, geospatial analysis, and statistical modeling. Experience with time series analysis, spatial mapping, and oceanographic data interpretation
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international users in water and food systems. Job Description: Over the past few years, advances in computational power and the increasing availability of large volumes of remote sensing data with finer spatial