{"id":4337,"date":"2026-05-25T15:02:06","date_gmt":"2026-05-25T10:02:06","guid":{"rendered":"https:\/\/propakistani.pk\/edunation\/?p=4337"},"modified":"2026-05-25T15:02:07","modified_gmt":"2026-05-25T10:02:07","slug":"how-to-study-in-sweden-with-the-doctoral-student-in-earth-observation-data-science-and-ai-for-poverty-estimation-scholarship-2026","status":"publish","type":"post","link":"https:\/\/propakistani.pk\/edunation\/guides\/how-to-study-in-sweden-with-the-doctoral-student-in-earth-observation-data-science-and-ai-for-poverty-estimation-scholarship-2026\/","title":{"rendered":"How to Study in Sweden With the Doctoral Student in Earth Observation, Data Science, and AI for Poverty Estimation Scholarship 2026"},"content":{"rendered":"\n

The Doctoral Student in Earth Observation, Data Science, and AI for Poverty Estimation Scholarship<\/a> 2026<\/strong> is a fully funded PhD opportunity<\/strong> offered by the Department of Computer Science and Engineering at Chalmers University of Technology<\/a> and the University of Gothenburg, Sweden<\/strong>.<\/p>\n\n\n\n

This research position focuses on using satellite imagery and artificial intelligence to estimate poverty levels across Africa<\/strong>, supporting global efforts to track and achieve the United Nations Sustainable Development Goals (SDGs)<\/strong>.<\/p>\n\n\n\n

About the Doctoral Student in Earth Observation, Data Science, and AI for Poverty Estimation Scholarship<\/h2>\n\n\n\n

This PhD project is part of the AI and Global Development Lab<\/strong> and the Observatory of Poverty programme<\/strong>, funded by the Swedish National Space Agency (SNSA)<\/strong>.<\/p>\n\n\n\n

For the 2026 intake<\/strong>, the position:<\/p>\n\n\n\n

    \n
  • Is a fully funded 4-year PhD (extendable to 5 years with teaching duties)<\/strong><\/li>\n\n\n\n
  • Includes collaboration between Chalmers University, University of Gothenburg, Link\u00f6ping University, and Harvard University<\/strong><\/li>\n\n\n\n
  • Focuses on AI for social good and poverty estimation using Earth Observation data<\/strong><\/li>\n\n\n\n
  • Uses satellite sources like Sentinel-2, Pl\u00e9iades, and Landsat<\/strong><\/li>\n\n\n\n
  • Combines machine learning, computer vision, and geospatial analysis<\/strong><\/li>\n\n\n\n
  • Requires the development of open-source tools for poverty estimation<\/strong><\/li>\n\n\n\n
  • Encourages publication in top venues like NeurIPS, ICML, Nature, and IEEE journals<\/strong><\/li>\n\n\n\n
  • <\/li>\n<\/ul>\n\n\n\n

    Why Choose The Doctoral Student in Earth Observation, Data Science, and AI for Poverty Estimation Scholarship?<\/h2>\n\n\n\n

    This PhD is ideal for students interested in combining AI, remote sensing, and social impact research<\/strong>.<\/p>\n\n\n\n

    At Chalmers University of Technology<\/strong>, students benefit from:<\/p>\n\n\n\n

      \n
    • World-class research in AI, data science, and Earth observation<\/strong><\/li>\n\n\n\n
    • Collaboration with top institutions like Harvard University and Link\u00f6ping University<\/strong><\/li>\n\n\n\n
    • Strong focus on real-world impact and sustainable development<\/strong><\/li>\n\n\n\n
    • Weekly international lab meetings and mentorship<\/li>\n\n\n\n
    • Opportunity to publish in top-tier AI and science journals<\/strong><\/li>\n\n\n\n
    • Exposure to interdisciplinary research across computer science, sociology, and geoscience<\/strong><\/li>\n<\/ul>\n\n\n\n

      Doctoral Student in Earth Observation, Data Science, and AI for Poverty Estimation Scholarship Summary<\/h2>\n\n\n\n
        \n
      • Host Country:<\/strong> Sweden<\/li>\n\n\n\n
      • Host Universities:<\/strong> Chalmers University of Technology & University of Gothenburg<\/li>\n\n\n\n
      • Research Lab:<\/strong> AI and Global Development Lab<\/li>\n\n\n\n
      • Position Type:<\/strong> Fully funded PhD (Doctoral student position)<\/li>\n\n\n\n
      • Field:<\/strong> Artificial Intelligence, Data Science, Earth Observation<\/li>\n\n\n\n
      • Focus Area:<\/strong> Poverty estimation using satellite imagery<\/li>\n\n\n\n
      • Funding Body:<\/strong> Swedish National Space Agency (SNSA)<\/li>\n\n\n\n
      • Duration:<\/strong> 4 years (extendable to 5 with teaching)<\/li>\n\n\n\n
      • Monthly Salary:<\/strong> ~34,550 SEK\/month (starting level)<\/li>\n\n\n\n
      • Deadline:<\/strong> 13 June 2026<\/li>\n<\/ul>\n\n\n\n

        Benefits<\/h2>\n\n\n\n

        Selected doctoral candidates receive:<\/p>\n\n\n\n

          \n
        • Full salary-based PhD funding (employee status)<\/li>\n\n\n\n
        • Monthly salary starting at 34,550 SEK<\/strong><\/li>\n\n\n\n
        • Tuition-free doctoral education<\/li>\n\n\n\n
        • Access to advanced AI and geospatial research infrastructure<\/li>\n\n\n\n
        • International collaboration opportunities (Sweden, USA, India, Chile, UK)<\/li>\n\n\n\n
        • Paid teaching opportunities (up to 20%)<\/li>\n\n\n\n
        • Strong career pathways in academia, the AI industry, and policy research<\/li>\n<\/ul>\n\n\n\n

          Eligibility Criteria<\/h2>\n\n\n\n

          Applicants must:<\/p>\n\n\n\n

            \n
          • Hold a Master\u2019s degree (or equivalent 4-year Bachelor\u2019s for some international systems)<\/strong> in:\n
              \n
            • Computer Science<\/li>\n\n\n\n
            • Data Science<\/li>\n\n\n\n
            • Statistics<\/li>\n\n\n\n
            • Mathematics<\/li>\n\n\n\n
            • Electrical Engineering<\/li>\n\n\n\n
            • Physics<\/li>\n\n\n\n
            • Computational Social Science or related fields<\/li>\n<\/ul>\n<\/li>\n\n\n\n
            • Have strong programming skills (Python, R, Julia, or C++)<\/li>\n\n\n\n
            • Experience with deep learning frameworks (PyTorch, TensorFlow, or JAX)<\/strong><\/li>\n\n\n\n
            • Strong English communication skills<\/li>\n\n\n\n
            • Demonstrate interest in interdisciplinary research and sustainability<\/strong><\/li>\n<\/ul>\n\n\n\n

              Preferred Skills<\/h2>\n\n\n\n

              Applicants with the following will have an advantage:<\/p>\n\n\n\n

                \n
              • Experience with satellite imagery or remote sensing data<\/strong><\/li>\n\n\n\n
              • Knowledge of geospatial tools (GDAL, rasterio, geopandas, Google Earth Engine)<\/strong><\/li>\n\n\n\n
              • Understanding of spatio-temporal machine learning models<\/strong><\/li>\n\n\n\n
              • Interest in causal inference and statistical modeling<\/strong><\/li>\n\n\n\n
              • Prior research publications or thesis work in AI or data science<\/li>\n\n\n\n
              • Experience in interdisciplinary or policy-oriented research<\/li>\n<\/ul>\n\n\n\n

                Required Documents<\/h2>\n\n\n\n

                Applicants must submit:<\/p>\n\n\n\n

                  \n
                • CV (including research and programming experience)<\/li>\n\n\n\n
                • Personal motivation letter<\/li>\n\n\n\n
                • Academic transcripts (Bachelor\u2019s and Master\u2019s)<\/li>\n\n\n\n
                • Thesis or research publications (if available)<\/li>\n\n\n\n
                • Reference contacts (requested later in the process)<\/li>\n<\/ul>\n\n\n\n

                  Application Process & Timeline<\/h2>\n\n\n\n
                    \n
                  1. Prepare CV, motivation letter, and academic documents<\/li>\n\n\n\n
                  2. Submit an application through the Chalmers recruitment system<\/li>\n\n\n\n
                  3. Shortlisted candidates are invited for interviews<\/li>\n\n\n\n
                  4. Final selection is made after the evaluation process<\/li>\n\n\n\n
                  5. Successful candidate begins PhD position in Sweden<\/li>\n<\/ol>\n","protected":false},"excerpt":{"rendered":"

                    The Doctoral Student in Earth Observation, Data Science, and AI for Poverty Estimation Scholarship 2026 is a fully funded PhD opportunity offered by the Department of Computer Science and Engineering at Chalmers University of Technology and the University of Gothenburg, Sweden. This research position focuses on using satellite imagery and artificial intelligence to estimate poverty […]<\/p>\n","protected":false},"author":5,"featured_media":4328,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[57],"tags":[],"class_list":["post-4337","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-guides"],"_links":{"self":[{"href":"https:\/\/propakistani.pk\/edunation\/wp-json\/wp\/v2\/posts\/4337","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/propakistani.pk\/edunation\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/propakistani.pk\/edunation\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/propakistani.pk\/edunation\/wp-json\/wp\/v2\/users\/5"}],"replies":[{"embeddable":true,"href":"https:\/\/propakistani.pk\/edunation\/wp-json\/wp\/v2\/comments?post=4337"}],"version-history":[{"count":1,"href":"https:\/\/propakistani.pk\/edunation\/wp-json\/wp\/v2\/posts\/4337\/revisions"}],"predecessor-version":[{"id":4338,"href":"https:\/\/propakistani.pk\/edunation\/wp-json\/wp\/v2\/posts\/4337\/revisions\/4338"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/propakistani.pk\/edunation\/wp-json\/wp\/v2\/media\/4328"}],"wp:attachment":[{"href":"https:\/\/propakistani.pk\/edunation\/wp-json\/wp\/v2\/media?parent=4337"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/propakistani.pk\/edunation\/wp-json\/wp\/v2\/categories?post=4337"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/propakistani.pk\/edunation\/wp-json\/wp\/v2\/tags?post=4337"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}