Postdocs in Computational Social Science

Work assignments 

Position description

This advertisement is for one to two postdoc positions on using machine learning and causal inference to evaluate the impact of local development programs in Africa. The candidate will work as part of an interdisciplinary team towards the goals of Observatory of Poverty project which is situated at the AI and Global Development Lab (you will find more information about the Lab at global-lab.ai) and The Institute for Analytical Sociology (IAS).

The vision of the Lab is to “combine AI, earth observation, and socio-economic theories to analyze sustainable and human development globally.” The Lab is mainly located at DSAI and IAS. The Swedish Research Council funds this Lab through a Research Environment Program and a Consolidator Grant. Pilot funding comes from Chalmers AI Research Centre (CHAIR). Google, in partnership with the Group on Earth Observations, provides mentorship and in-kind technical support for the Lab.

The IAS is a highly international, interdisciplinary research center located in Norrköping, Sweden, with a PhD program in Analytical Sociology and an international Masters’ program in Computational Social Science. The research strengths of the IAS include the study of social mobility, cultural sociology, political sociology, organizational theory, social network analysis, and computational text analysis.  More information can be found here: https://liu.se/en/organisation/liu/iei/ias

About the project

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. As this challenge is already being handled by our team at the AI and Global Development Lab, the prospective candidate will join the Lab to use these data for evaluating the effect of local development programs, using a causal-inference design.

Thus, the candidate will contribute to the following goal: to use our data to identify to what extent African communities are trapped in poverty and explain how competing development interventions alter these communities’ prospects to free themselves from deprivation. To achieve this goal, the project will tackle the following objectives:

The project aims to primarily focus on (1) developing methods for estimating poverty by combining remote sensing (i.e., satellite images) with machine learning and (2) developing causal inference methods using satellite images for evaluating various development projects (e.g., Chinese or World Bank) in Africa. The candidate is expected to primarly select on of these aims, and therefore, that selection should be clearly indicate in the application.

Job expectations and opportunities

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 two 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.

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

We are committed to providing high-quality mentorship for the candidate (see below for more information about the mentorship).

Duties

Project duties include primarily to lead articles that are publishable in highly ranked journals and contribute to other research within the framework of the research project. Attending weekly Lab meetings and presenting ongong work is also part of the duties. Contributions to methodologically oriented journals and conference proceedings can also be part of the work, depending on the interest of the applicant.

Qualifications

The position requires a doctorate or an equivalent degree from a foreign university. Candidates who have their Ph.D. defense in close foresight are also eligible to apply.

As the project is highly interdisciplinary, we welcome applicants from a variety of social-scientific disciplinary backgrounds, such as sociology, economics, political science, development studies, data science, or social epidemiology. That includes sub-fields (but not restricted to) such as computational social science, political economy, economic sociology, development economics, social determinants of health, poverty, inequality, global issues, sustainable development, and methodology. For those candidates interested in methodology, we can tailor the position so that it aims to conduct methodological development for causal inference in the context of the listed objectives.

Regardless of academic background, to contribute to this research, the candidate should posses the following skills and experiences:

1. Excellent communication skills in written and spoken English.
2. Excellent coding skills in R, Python, or equivalent language.
3. Research interest in causal inference (see e.g., Morgan and Winship, 2014, Counterfactuals and Causal Inference or Imbens and Rubin, 2015, Causal Inference for Statistics, Social, and Biomedical Sciences, or Pearl, 2016, Causal Inference in Statistics)
4. Training deep learning models at scale on compute clusters.
5. The candidate should have a proven track record in producing academic articles. Such proof preferably entails attaching a publication in high-quality peer-reviewed journals or at least a working-paper manuscript.

Desirable skills and experience include:

6. Working with temporal and geographical data (or willingness to learn using such data).
7. Experience in using machine learning models is welcomed (or willingness to learn using such models).
8. Research interest in global development, poverty, inequality, or governance, international institutions, Chinese politics, World Bank, social demography, political sociology, or political economy.

The workplace

Work environment

While we encourage the candidate to physically move to Norrköping Sweden, we might offer the possibility of working remotely for a certain part of your working time when the needs of the project and the tasks allow this. 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 and the Observatory of Poverty project are headed by Adel Daoud, and will be the main mentor for the candidate (more information is provided at www.adeldaoud.com). A second mentor will be Connor Jerzak at the University of Texas at Austin (www.connorjerzak.com).

Jerzak received his Master’s in Statistics and Ph.D. in Government from Harvard University, where he was advised by Gary King, Kosuke Imai, and Xiang Zhou. Connor completed a one-year postdoc with Adel Daoud and the AI and Global Development Lab at Linköping University (Sweden) while serving as a Visiting Scholar in the Program on Governance and Local Development (GLD) at the University of Gothenburg. Since 2022, he has served at the University of Texas at Austin as an Assistant Professor in the Department of Government.

Daoud is a Senior Associate Professor at IAS, 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. Daoud leads The AI and Global Development Lab (global-lab.ai). Previously he held positions at Harvard University, the University of Cambridge, the Max Planck Institute for the Studies of Societies, and the Alan Turing Institute. His research has both a social-scientific and methodological orientation. For the social sciences, he researches the effect of international development interventions on global poverty, but also the impact of sudden shocks (e.g., economic, political, and natural disasters). Daoud implements novel methodologies in machine learning and causal inference to analyze the causes and consequences of poverty and inequality. He has published in journals such as PNAS, Science Advances, or World Development, includig machine-learning conferences such as the Association for the Advancement of Artificial Intelligence (AAAI) and the North American Chapter of the Association for Computational Linguistics (NAACL). In 2022, Daoud was awarded the Hans L. Zetterberg Prize in Sociology which is given annually to young researchers, who with their scholarly work in sociology, preferably by fruitfully combining theory and practice, have advanced the research front. He is also a member of the Swedish Young Academy, which gathers a selection of the top scholars in Sweden across all disciplines.

Daoud, Jerzak, and other members of 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):

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.

The employment

This employment is a temporary contract of two years with the possibility of extension up to a total maximum of three years. 

Background screening may come to be carried out before any decision on employment is made.

Salary and employment benefits

The University applies individual salary scales adapted to the experience of the employee and to the labour market.

More information about employee benefits is available here.

Union representatives

Information about union representatives, see Help for applicants.

Application procedure

Apply for the position by clicking the “Apply” button. Your application must be received no later than 19th of May 2025. 

In addition to what is requested in the application form we want you to attach a working sample, proof preferably a publications in a peer-reviewed journal or at least a working-paper manuscript, demonstrating your flagship work.

Applications and documents received after the date above will not be considered. 
 
Please attach your selected research publications electronically, in pdf or word format, in the application template. Research publications, e.g. monographs, which cannot be sent electronically should be sent in three sets by mail to the University Registrar at Linköping University, University Registrar, S-581 83 Linköping, Sweden. The publications must be received by Linköping University no later than the deadline for application. 

Please note that printed publications will not be returned. They will be archived at Linköping University. 
 
In the event of a discrepancy between the English translation of the job announcement and the Swedish original, the Swedish version shall take precedent.