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Field
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from buildings, mobile network data) Database management skills (e.g., PostgreSQL) Statistical expertise related to big data processing and high-performance computing (Python, R) GIS software proficiency
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, multi-level, discrete choice behavior modeling…) based on statistical software (R, STATA or SAS) ;Excellent skills in GIS and Python are an asset ;Excellent communication and collaboration skills
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, preferably in agriculture or mining environments. Strong expertise in hyperspectral remote sensing and geographic information science (GIS) for mapping and monitoring agricultural soils and vegetation at field
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. PhD degree in Hydrology, Environmental Science, Civil Engineering, or a related field. Experience with hydrological models (e.g., SWMM, HEC-RAS, Delft-FEWS, CityCAT). Proficiency in GIS tools, remote
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., Python, R) and GIS tools (e.g., QGIS) experience. Excellent communication skills. Strong publication record related to current position
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from buildings, mobile network data) Database management skills (e.g., PostgreSQL) Statistical expertise related to big data processing and high-performance computing (Python, R) GIS software proficiency
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techniques, by powder diffraction, PDF analysis, GI-PDF, and complementary characterization techniques, e.g. IR Experience in material synthesis Motivated and creative approach to research with the ability
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proficiency in languages such as R and Python. Experience in GIS, remote sensing, and processing projected climate data. Proven ability to manage multiple tasks effectively, work collaboratively in team
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familiarity with model coupling frameworks (e.g., ESMF). Proficiency in programming and data analysis (e.g., Python, Fortran) and handling large datasets, including GIS or remote sensing integration. Strong
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or related fields programming experience in Python or extensive experience in another high-level programming language is a prerequisite experience in geospatial data science, remote sensing, GIS, and open