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Doctoral student in Earth Observation, Data Science, and AI for poverty

Göteborg, Sweden💼 Full-time🗓 2026-05-13 → 2026-06-24

Core

Develop deep-learning methods to estimate multidimensional poverty from satellite imagery of African communities and evaluate progress toward Sustainable Development Goals.

Role type

Doctoral student (researcher)

Builds

Deep-learning models for poverty estimation, open-source statistical software

Domain

Earth Observation, Data Science, AI for Social Good

Deliverable

production ML models | research

Required skills

deep learning, satellite imagery analysis, statistical learning theory, machine learning

Preferred skills

explainability methods, computational cost analysis, interdisciplinary collaboration

Technologies

Sentinel-2, Pléiades, Landsat

Responsibilities

Develop deep-learning methods for poverty estimation from satellite imagery, compare satellite data quality and computational costs, apply AI explainability methods to model predictions

Seniority

Doctoral student (early career researcher)

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