About the program:

The Ross Center for Sustainable Cities (https://www.wri.org/cities) builds on WRI’s global and local experience in urban planning and mobility and uses proven solutions and action-oriented tools to make the fast-growing urban environment more resilient to new challenges. The Urban Development Program (https://www.wri.org/cities/urban-development) is committed to designing and influencing urban spaces that build resilience, improve health, and equitably connect people and opportunities. As part of the Data For Cool Cities Initiative , our data team is developing geospatial datasets, analytics and tools to support urban decision makers in implementing cooling infrastructure for reducing population exposure to extreme heat.

Internship Highlight:

In the internship, you will:

  • Collect, document, clean and analyze geospatial data for better assessing urban heat stress in different European Cities (Land Surface Temperature, Air temperature, tree canopy, buildings)
  • Perform data analysis on existing data, and support research for identifying alternative data sources (specific for European context) and calculating geospatial indicators
  • Develop spatial analysis and produce static and interactive maps for addressing use cases identified by our stakeholders: identifying urban hotspots, mapping priority areas for implementing cooling infrastructure, estimating cooling benefits of various cooling interventions scenarios, estimating population exposure to extreme heat
  • Implement heat resilient infrastructure scenarios using urban heat model and estimating cooling impact and benefits of multiple heat resilience interventions

    You will be supported by the Cities Data team and Data lab colleagues: Data scientist, data engineers, heat-health specialists. And you will be collaborating with the Global Cities Data team in different WRI country offices (Mexico, India, Africa, Brazil)

    You will report to the Data Product Manager of the Cities Data team.

    What you will do:

    • You will contribute to advancing Urban heat modeling activities for and developing research for measuring the cooling benefits of Nature Based Solutions in Europen cities
    • You will learn to analyze large geospatial data and use cloud infrastructure for solving climate challenges and extracting insights using geostatistics and machine learning techniques
    • You will help in transforming data into recommendation for policy makers and city officials to drive urban planning strategies and climate action implementation. you will learn experience in documenting code, methodology and datasets
    • You will gain experience in developing compelling storytelling based in data visualization and maps and participate in writing blog posts to share research findings with the public.

      What you will need:

      • Interns at WRI Europe must be registered in a study program with a Dutch college or university for the full duration of the internship
      • Interns must have established approval from their University to undertake an internship before applying
      • Currently pursuing a degree in GIS, Geo-information and earth observation computer science, data science, computational urban planning, quantitative geography, environmental modelling
      • Must be registered in a study program with a Dutch college or university for the full duration of the internship
      • Confident use of Python and/or R
      • Familiarity with Geographic Information Systems (GIS), spatial analysis tools (QGIS, Google Earth Engine, Carto) and geospatial libraries (rasterstat, xarray, shapefile, geopandas, sf, rasterio, gee)
      • Familiarity with working with geospatial datasets (satellite imagery, climate data, census, urban features) and geospatial data formats (both raster and vector data)
      • Familiarity with statistics and geo-statistics concepts and methods
      • Strong written and verbal communication skills
      • Ability to document methodology
      • Verbal and written proficiency in English.

        Conditions of the internship:

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