Postdoc in developing deep learning for satellite images

Ref REF 2022-0869

This is a call for one postdoctoral position in the Data Science and AI division at the Department of Computer Science and Engineering, Chalmers University of Technology. The positions are situated within the research project Observatory of Poverty, situated in the AI and Global Development Lab (you will find more information about the Lab at, funded by the Swedish Research Council (SRC). The Lab furthers the use of AI for Social Good for the sustainable development goals.

Project description
About 900 million people—one-third in Africa—live in extreme poverty. Operating on the assumption that life in impoverished communities is fundamentally so different that it can trap people in cycles of deprivation (‘poverty traps’), major development agencies have deployed a stream of development projects to break these cycles (‘poverty targeting’). However, scholars are currently unable to answer questions such as in what capacity do poverty traps exist; to what extent do these interventions release communities from such traps—as they are held back by a data challenges. This challenge is that there is a lack of geo-temporal poverty data, and thus, one of the goals of the Observatory of Poverty project is to develop new methods to produce such data. Thus, this is the main challenge that the postdoc is expected to contribute to.

1.To train learning algorithms to estimate poverty from satellite images, of African communities over time and space, quarterly, from 1984 to 2020.
2.To contribute to creating a statistical package—ObservatoryOfPoverty—that enables us, and other scholars, to produce poverty estimates for policy evaluation.

Another goal of the Observatory of Poverty is to use our poverty estimates to identify to what extent African communities are trapped in poverty and explain how competing aid and development interventions alter these communities’ prospects to free themselves from deprivation. This goal is about causal inference. Thus, a secondary goal of the postdoc position is to facilitate the methodological development for causal inference for the project.

In other words, we are searching for a candidate that is interested in either poverty estimation from satellite images or the causal inference part of the project, or both. Your interest should be clearly stated in your application and linked to your track-record.

The candidate for the postdoc position will join the AI and Global Development Lab and is expected to produce research that contributes to the listed objectives or related spin-off objectives (e.g., based on the candidate’s research interest). Such spin-offs are welcomed, especially those that provide a new research angle to the listed objectives.

As the project is highly interdisciplinary, we welcome applicants from a variety of disciplinary backgrounds, such as computational social science, statistics, computer science, mathematics, information technology, computer or electrical engineering, signal processing, physics or related fields, and experience in machine learning.

We publish in top interdisciplinary generalist journals, discipline-specific journals, and conferences. We will adapt our publication strategy depending on the candidate’s background and interest.

Regardless of background, to contribute to this research, the candidate should have experience in the following items:

  1. Excellent communication skills in written and spoken English.
  2. Excellent coding skills in Python, R, or equivalent language
  3. Experience in using deep learning.
  4. Experience in image processing, preferably satellite images

Desirable skills and experience are the following:

  1. Experience in remote sensing or earth observations (or willingness to learn)
  2. Experience in using Google Earth Engine (or willingness to learn)
  3. Research interest in causal inference (or willingness to learn) (see e.g., Imbens and Rubin, 2015, Causal Inference for Statistics, Social, and Biomedical Sciences, or Pearl, 2016, Causal Inference in Statistics).

The candidate should have a proven track record in applying deep-learning methods with publications in peer-reviewed journals or conferences.

Work environment
The AI and Global Development Lab tend to meet weekly and remotely, with collaborators based in Sweden, the United States, India, Chile, United Kingdom.

The project constitutes a collaboration mainly among the Department of Engineering and Computer Science, Chalmers University of Technology, the Departments of Political Science, University of Gothenburg, Institute for Analytical Sociology, Linköping University (campus Norrköping) and the Department of Statistics, Harvard University. This means that occasional travels within Sweden and between Sweden and the United States are expected.

Leadership and mentorship
The AI and Global Development Lab are headed by Adel Daoud, and will be the primary mentor for the candidate (more information is provided at Daoud is a computational social scientist. He is a Senior Associate Professor at the Institute for Analytical Sociology, Linköping University, and an Affiliated Associate Professor in Data Science and Artificial Intelligence for the Social Sciences, Department of Computer Science and Engineering, Chalmers University of Technology, Gothenburg, Sweden. Previously he held positions at Harvard University, the University of Cambridge, and the Alan Turing Institute. The vision of the Lab is to “combine AI, earth observation, and socio-economic theories to analyze sustainable and human development globally.”

The two secondary mentors will be Connor Jerzak at the University of Texas at Austin (, and Mohammad Kakooei, at DSAI. Other important collaborators to the projects and potential mentors are Fredrik Johansson (DSAI), Devdatt Dubhashi (DSAI), and Xiao-Li Meng (Harvard).

Daoud, Jerzak, Kakooei, and others at the Lab are committed to providing high-quality mentorship for the candidate. For example, Daoud is the creator of a new podcast called the Journeys of Scholars. The Journeys of Scholars is a podcast with conversations about the trajectories, macro-micro strategies, habits, and advice of top-class academic performers.

The candidate is encouraged to check out the YouTube playlist (provided here) and some of the recent interviews are the following:
• Pursuing excellence. An interview with Professor Gary King, Harvard University. (Link to the show)
• How to combine academia and entrepreneurship. Continuing the conversation with Prof. King at Harvard. (Link to the show)
• Following your curiosity. Interview with Xiao-Li Meng, Professor of Statistics, Harvard University. (Link to the show)
• Establishing your research program. An Interview with Prof. Stephen Raudenbush University of Chicago. (Link to the show)
• Choosing your academic path. Interview with Professor Christopher Winship, Harvard University. (Link to the show)
• Building excellent research environments. Interview with Professor Peter Hedström, Linköping University. (Link to the show)
• Finding one's path as a statistician or data scientist. An Interview with Prof. Jennifer Hill, New York University. (Link to the show)

The applications
the Application must be received by the application deadline, listed below. Apply for the position by clicking the “Apply” button below. The application should include the following items.

  1. First, the candidate is expected to attach a working sample, proof preferably a publications in a peer-reviewed journal or at least a working-paper manuscript, demonstrating the flagship work of the candidate.
  2. Second, the candidate should include a prospective project plan (max 1000 words), describing how the candidate’s research background is suitable for tackling the project objectives stated previously. Alternatively, the candidate should describe what related spin-off objectives the candidate would like to pursue instead, based on the candidate’s research interest.
  3. Third, the application should include a short cover letter (max 400 words), addressing the candidate’s academic background, and how the position furthers the candidate's future aspirations.
  4. Fourth, CV (Please name the document as: CV, Surname, Ref. number) CV, include complete list of publications. Previous teaching and pedagogical experiences and two references that we can contact.
  5. Fifth, attested copies of completed education, grades and other certificates.

The application should be marked with Ref 20220684 and written in English. The application should be sent electronically and be attached as PDF-files. Maximum size for each file is 40 MB. Please note that the system does not support Zip files.

Working and living in Sweden
Sweden offers one of the most high-quality living standards in the world. It provides a great welfare system, with government-funded health care and education. This means that schooling and health care are virtually free, saving some minor costs. For a postdoc provides for more than compared to other postdoc salaries around the world.

Major responsibilities
The main responsibility of the candidate will be to pursue research in the area of the position. The candidate will have the chance to work with the group members and collaborators at Chalmers and abroad, including the co-supervision of PhD students. The candidate is encouraged to supervise/teach up to 20% of their time.

Contract terms
Full-time temporary employment. The employment is limited (temporary) for 24 months with the possibility of extention with 12 months (contingent on funding and research performance).

Applicants must have a doctorate, PhD or equivalent degree, in a relevant field.  The degree should generally not be older than three years, but exception can be made.

To qualify, candidates must have experience in one or more of (1) deep learning, (2) causal inference (3) image data (preferably earth observations), (4) modeling geo-temporal data, as evidence by publications in appropriate venues. 

The position requires sound verbal and written communication skills in English. Swedish is not a requirement

We offer

Chalmers offers a cultivating and inspiring working environment in the coastal city of Gothenburg
Read more about working at Chalmers and our benefits for employees.

Chalmers aims to actively improve our gender balance. We work broadly with equality projects, for example the GENIE Initiative on gender equality for excellence. Equality and diversity are substantial foundations in all activities at Chalmers.

Application deadline: February 20 , 2023

For questions, please contact:
Adel Daoud, CSE DSAI

*** Chalmers declines to consider all offers of further announcement publishing or other types of support for the recruiting process in connection with this position. *** 

Chalmers University of Technology conducts research and education in engineering sciences, architecture, technology-related mathematical sciences, natural and nautical sciences, working in close collaboration with industry and society. The strategy for scientific excellence focuses on our six Areas of Advance; Energy, Health Engineering, Information and Communication Technology, Materials Science, Production and Transport. The aim is to make an active contribution to a sustainable future using the basic sciences as a foundation and innovation and entrepreneurship as the central driving forces. Chalmers has around 11,000 students and 3,000 employees. New knowledge and improved technology have characterised Chalmers since its foundation in 1829, completely in accordance with the will of William Chalmers and his motto: Avancez!


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