Research Engineer at the Institute for Analytical Sociology

We seek to fill one or several research engineer at the Institute for Analytical Sociology (IAS). IAS is an interdisciplinary research center on the intersection of analytical sociology and computational social science. The position is advertised within the research project Observatory of Poverty.

The position

This advertisement is for a candidate that will use 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 www.aidevlab.org ) 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 administratively located at IAS and The Division of Data Science and Artificial Intelligence of the Department of Computer Science and Engineering, Chalmers University of Technology, Gothenburg, Sweden. The Lab consists of members in these institutions as well as Harvard University, University of Texas at Austin, and other universities. 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, provided mentorship and in-kind technical support to kick start 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. 

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:

To examine how World Bank (WB) development programs versus Chinese programs, select African communities, and how these affect communities’ chances of breaking the cycle of deprivation (using the data of Obj1).

To develop theories of the varieties of poverty traps by examining the extent to which these traps lurk in different social contexts that shape both local governance and public-service provisioning, and how these contexts may be more or less important for Chinese- or WB-styled projects.

To support in training computer vision models and LLMs for improving poverty map estimation.

Thus, the main duties are.

1. Prepare geo-temporal data for causal inference.
2. Lead and support research articles based on the two topics listed.
3. Conduct reviews of literature, synthesize key findings, and remaining research questions.

Qualifications

Applicants should have:

• A bachelor’s or master’s degree in the social sciences (e.g., economics, sociology, political science) with a strong quantitative and computational focus, or a corresponding degree in computer science, data science or statistics with interest in AI for Social Good.

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. Research interest in computer vision and earth observations.

Desirable skills and experience include:

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

The workplace

The workplace will be the Institute for Analytical Sociology at Campus Norrköping, Linköping University.

The employment

The employment is part or full-time for 12 months. Employment will begin as soon as possible.

Salary and employment benefits

The university applies individual salaries. 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 below. Your application must reach Linköping University no later than November 7, 2025.

Applications and documents received after the date above will not be considered.