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Field
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skills (one or more of the following strongly desired) Exploratory analysis of massive datasets (machine learning methods) Spatial data analysis and Geographic Information Systems (GIS) Forecasting and
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), or Remote sensing and GIS We welcome innovative research ideas beyond these examples, provided they align with the broader themes of ecosystem processes and disturbance ecology. The anticipated project
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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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automating geospatial workflows. Proficiency with GIS tools (e.g., QGIS, ArcGIS) for spatial analysis and visualization. Experience developing statistical or machine learning models to estimate fuel moisture
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FieldEnvironmental scienceYears of Research ExperienceNone Additional Information Eligibility criteria PhD Thesis in population ecology Skills in data analysis, GIS data and database management Skills in writing
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project and specifically on developing a GIS-based decision support system for 15-min city and micromobilityanalysis for several European cities. Weexpect a motivatedearlycareer researcher with
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interventions. •Integration of spatial (GIS) and socioeconomic data with urban transformation indicators (iBESTI). •Writing of scientific articles in high-impact international journals and participation in
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socioeconomic and environmental data. • Development and application of indicators to measure social and environmental justice in 15-minute city scenarios. • Integration of spatial data (GIS) and sources
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are seeking a postdoctoral researcher specializing in digital technologies and urban health. The successful candidate will develop innovative solutions based on the analysis of urban data (big data, IoT, GIS
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monitoring using SAR and multi-spectral images, GIS, scientific programming - English proficiency, team work, reporting, redaction of scientific publication, organization and project management