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Field
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GIS software and Python, strong written and interpersonal communication skills, and a demonstrated interest in addressing social justice issues through data-driven research. The postdoc will work in
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Institut Pierre Louis d'Epidémiologie et de Santé Publique (IPLESP) | Paris 15, le de France | France | about 3 hours ago
Expertise in Geographic Information Science (GIS), including proficiency with ArcGIS Pro General knowledge of urban geography Strong interest in the interactions between climate change and human health in
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. Experience with trait-based ecology, ecometric or functional-trait modeling, or macroecological analyses. Experience with R, Python, or equivalent programming languages for statistical and spatial analyses
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background in machine learning, predictive modeling, or applied AI Proficiency in Python and/or R; experience with libraries like scikit-learn, XGBoost, TensorFlow. -Experience working with real-world datasets
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with Microsoft Office Suite and familiarity with statistical and geospatial software such as Python, R, and GIS applications (e.g., ArcGIS, QGIS). Ability to work collaboratively as part of a
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qualifications in probilistic risk modelling, applied statistics and familiar with quantitative risk modelling measures strong data analysis skills and proficiency in R and Python; experience with other programing
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, and statistical analysis. Proficiency in data analytics, visualization. Proficiency in at least one of the following programming languages: R or Python. Proficiency in Microsoft Office (including
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predictive modelling Public policy evaluation Management and analysis of survey data Software proficiency Statistical and econometric packages such as Stata, R, or Python GIS software (QGIS, ArcGIS
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; - No employment contract, or proof of full unpaid leave, in accordance with FAPESP regulations . Desired Skills: - Proficiency in R, Python, and JavaScript (Google Earth Engine); - Geoprocessing and GIS
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. Excellent proficiency in spatial and statistical programming (e.g., R, Python, or Google Earth Engine). Proficiency in, and commitment to, version control (e.g., Git), reproducible research practices, and