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

Doctoral student in Earth Observation, Data Science, and AI for poverty estimation Can satellites see poverty—and can AI help end it? We are looking for a Doctoral student to develop deep-learning methods that estimate living conditions across Africa from satellite imagery, and to compare different satellites for this purpose. Then, we use these estimates to evaluate how well villages and cities in Africa and beyond will achieve the Sustainable Development Goals. You will be mentored by an interdisciplinary team and join an internationally connected lab committed to your growth as a researcher. About us The https://www.chalmers.se/en/departments/cse/, a joint department of Chalmers and the University of Gothenburg, spans the breadth of computing disciplines. Our internationally visible research, strong industry links and diverse environment create a collaborative setting where ideas grow into real impact. At the https://www.chalmers.se/en/departments/cse/our-research/data-science-and-ai/, we develop data-driven methods and AI solutions that support intelligent decisions across society, advancing machine-learning techniques from foundations to industrial and scientific applications. About the Lab The position is hosted by the http://www.aidevlab.org based at the Division of Data Science and AI (DSAI), Department of Computer Science and Engineering, Chalmers University of Technology, and the Institute for Analytical Sociology, Linköping University. The Lab advances the use of AI for Social Good in pursuit of the Sustainable Development Goals. The Lab brings together collaborators in Sweden, the United States, India, Chile, and the United Kingdom, and publishes in top interdisciplinary generalist journals, discipline-specific journals, and AI conferences. Because the work is highly interdisciplinary, we welcome candidates from a range of backgrounds and adapt our publication strategy to the doctoral student’s interests and trajectory. Work environment The Lab meets weekly, both in person and remotely, with collaborators across multiple time zones. The doctoral project is a collaboration mainly among the Department of Computer Science and Engineering at Chalmers, the Department of Earth Sciences at the University of Gothenburg, the Institute for Analytical Sociology at Linköping University (campus Norrköping), and the Department of Statistics at Harvard University. Occasional travel within Sweden and abroad is part of the role. Leadership and mentorship The Lab is headed by http://www.adeldaoud.com, who will serve as the principal supervisor. Daoud is Professor of Computational Social Science at the Institute for Analytical Sociology (Linköping University) and Affiliated Associate Professor in Data Science and AI for the Social Sciences at Chalmers. He has previously held positions at Harvard University, the University of Cambridge, and the Alan Turing Institute. The secondary supervisor is Ashkan Panahi, Associate Professor in the Division of Data Science and AI at Chalmers, who works at the interface of machine learning, signal processing, and statistical learning theory. Additional mentors include senior Lab members and collaborators such as http://www.connorjerzak.com (University of Texas at Austin), Mohammad Kakooei (Karlstad University), Devdatt Dubhashi (DSAI, Chalmers), Xiao-Li Meng (Harvard), and James Bailie (DSAI, Chalmers). The Lab is committed to providing high-quality mentorship. The candidate is encouraged to explore the Journeys of Scholars podcast (created by Daoud), which features conversations about the trajectories, strategies, and advice of leading academics—available on YouTube and Spotify: https://www.youtube.com/@thejourneysofscholars8820 About the research project About 900 million people—one third in Africa—still live in extreme poverty. Scholars and policymakers lack the fine-grained geo-temporal data needed to identify which communities are reaching the Sustainable Development Goals and which interventions are working. The doctoral project, “Comparing Earth Observation and AI Methods for Sustainable Development,” is funded by the Swedish National Space Agency (SNSA / Rymdstyrelsen) and runs within the Lab’s Observatory of Poverty programme. The project pursues three objectives: Develop deep-learning methods that estimate multidimensional poverty from Sentinel-2 satellite imagery of African communities over time and space. Compare the quality and computational cost of poverty estimates produced from satellites with different resolutions—Pléiades (2 m), Sentinel-2 (10 m), and Landsat (30 m)—to identify the optimal trade-off between precision and cost. Apply AI explainability methods to understand what visual features drive the model’s poverty predictions, and to build trust in earth-observation-based estimates for policy use.

The doctoral student will lead all three work packages in close collaboration with the supervision team and contribute to the ObservatoryOfPoverty open-source statistical software. More information: www.aidevlab.org Application procedure To read more about the position and apply, please go to the Chalmers' vacancy page: https://www.chalmers.se/en/about-chalmers/work-with-us/vacancies/?rmpage=job&rmjob=14818&rmlang=UK  Please note: The applicant is responsible for ensuring that the application is complete. Incomplete applications and applications sent by email will not be considered. Contact details for references will be requested after the interview. We welcome your application no later than 13 June 2026. For questions, please contact: Adel Daoud Professor of Computational Social Science (Linköping University); Affiliated Associate Professor in Data Science and AI for the Social Sciences (Chalmers University of Technology); Head of the AI and Global Development Lab Email: daoud@chalmers.se We look forward to your application! Chalmers declines to consider all offers of further announcement publishing or other types of support for the recruiting process in connection with this position.