Background/Organizational Context

The Smart Parcel Atlas for Resilient Cities (SPARC) is a World Bank Group geospatial intelligence initiative that helps task teams and city governments generate and apply parcel-level spatial evidence for urban planning, infrastructure prioritization, land management, disaster risk management, and investment decisions. SPARC combines satellite imagery, global datasets, GeoAI methods, and administrative information to produce decision-ready layers on buildings, parcels, land use, infrastructure access, hazard exposure, population dynamics, and urban growth. The internship will support the thematic expansion of SPARC to conflict-affected and reconstruction contexts (e.g., South Sudan, Sudan, Ukraine), with a focus on how parcel- and neighborhood-level geospatial intelligence can inform remote monitoring, damage and change detection, population and displacement dynamics, service disruption analysis, and operational prioritization for recovery and resilience investments.

Duties and Responsibilities

• Review SPARC materials, reconstruction, and forced displacement use cases, and good practice on remote monitoring, damage detection, displacement tracking, and urban recovery analytics.
• Map relevant conflict-specific (including forced displacement) data sources and methods, including satellite imagery, building footprints, road networks, land cover, nighttime lights, population proxies, hazard exposure layers, and administrative datasets.
• Support definition of SPARC use cases for conflict and post-conflict settings, including reconstruction prioritization, service disruption screening, and remote supervision of recovery investments.
• Contribute to analytical frameworks, prototype analytics, mock-ups, and concise operational materials for selected contexts, subject to data availability and team priorities.
• Prepare notes, briefs, slide inputs, and documentation on data quality, uncertainty, limitations, validation needs, ethical considerations, and appropriate use in sensitive FCV contexts.

Selection Criteria

• Candidates must be currently enrolled in, or in the final year of, a postgraduate master’s or PhD program.
• Candidates must have 1–6 years of relevant professional experience
• Academic background in urban planning, geography, geospatial analytics, data science, remote sensing, international development, public policy, disaster risk management, conflict studies, economics, or a related field.
• Demonstrated interest in applying geospatial data and analytics to urban resilience, reconstruction, FCV, displacement, service delivery, or infrastructure planning.
• Strong analytical, research, and problem-solving skills, including ability to synthesize technical material for non-specialist audiences.
• Experience with GIS, remote sensing, spatial data management, Python/R, Google Earth Engine, QGIS or ArcGIS, or related tools.
• Ability to work effectively in diverse, team-based environments
• Excellent written and spoken English; knowledge of Arabic, Ukrainian, French, Amharic, Swahili, or other relevant languages is an asset.

• Review SPARC materials, reconstruction, and forced displacement use cases, and good practice on remote monitoring, damage detection, displacement tracking, and urban recovery analytics.
• Map relevant conflict-specific (including forced displacement) data sources and methods, including satellite imagery, building footprints, road networks, land cover, nighttime lights, population proxies, hazard exposure layers, and administrative datasets.
• Support definition of SPARC use cases for conflict and post-conflict settings, including reconstruction prioritization, service disruption screening, and remote supervision of recovery investments.
• Contribute to analytical frameworks, prototype analytics, mock-ups, and concise operational materials for selected contexts, subject to data availability and team priorities.
• Prepare notes, briefs, slide inputs, and documentation on data quality, uncertainty, limitations, validation needs, ethical considerations, and appropriate use in sensitive FCV contexts.

• Experience with GIS, remote sensing, spatial data management, Python/R, Google Earth Engine, QGIS or ArcGIS, or related tools.
• Ability to work effectively in diverse, team-based environments
• Excellent written and spoken English; knowledge of Arabic, Ukrainian, French, Amharic, Swahili, or other relevant languages is an asset.

• Candidates must be currently enrolled in, or in the final year of, a postgraduate master’s or PhD program.
• Candidates must have 1–6 years of relevant professional experience
• Academic background in urban planning, geography, geospatial analytics, data science, remote sensing, international development, public policy, disaster risk management, conflict studies, economics, or a related field.
• Demonstrated interest in applying geospatial data and analytics to urban resilience, reconstruction, FCV, displacement, service delivery, or infrastructure planning.
• Strong analytical, research, and problem-solving skills, including ability to synthesize technical material for non-specialist audiences.