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tools, data science techniques, and spatial analysis to leverage big data from cities and model their evolution. Main Tasks and Responsibilities: Collect, clean, and structure large volumes of urban
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have expertise in geometallurgy, applied geochemistry, and geo-environmental assessment, with advanced proficiency in integrating spatial data into 3D models using sophisticated interpolation techniques
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implications for access to basic services. Develop mapping and modeling tools to visualize socio-spatial inequalities. Perform comparative studies on public policies designed to reduce territorial divides
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. Contribute to the supervision of master and PhD students. Qualifications: Ph.D. in Earth Sciences, Remote Sensing, Physics, Applied mathematics, or related field. Strong background in land surface modeling
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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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digital twins to develop innovative solutions for monitoring, analyzing, and optimizing urban systems in real time. The candidate will contribute to modeling interactions between physical and digital
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properties in drylands worldwide and analyzing their spatial distribution. The research will utilize innovative remote sensing techniques, advanced modeling frameworks, and cutting-edge datasets to enhance our
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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