PhD candidate in Machine Learning-Informed Formal Theory Construction

Do you want to shape the future of social scientific research? Then join our team as a PhD student to co-develop machine learning-informed methods for theory construction. 

Theories describe scientists’ understanding of phenomena. Ideally, theories are used to derive hypotheses, and continuously updated based on new insights. In practice, many scientific fields focus near-exclusively on conducting empirical studies, skipping the important step of revising theory based on the ressults. In this PhD project, you will develop methods to help applied (social) scientists construct theories based on data patterns identified with causal discovery and interpretable machine learning.

Your position 
As a PhD candidate, you will conduct independent empirical and methodological research in the areas of interpretable machine learning and causal discovery. You will work towards the goal of developing and validating a workflow for constructing formal theories from patterns in empirical data. Each year, you will address a different milestone in pursuit of this goal:

• Benchmarking causal discovery methods on social science data
• Comparing the performance of different interpretable machine learning methods on social science data
• Developing the basic functionality for machine learning-informed theory construction as open source software
• Extending the basic functionality in one of several possible directions, based on your interests

This PhD project is part of a NWO Vidi project awarded to dr. Caspar J. Van Lissa (Dept. of Methodology & Statistics), who will serve as daily supervisor and will be available for daily check-ins and weekly scheduled meetings. The larger supervision team will consist of 2 or 3 members, to be determined based on your interests and needs, and will meet monthly. You will be part of a cohort with one other PhD student in the first year, and another who will join in the second year. You will be embedded in the newly established international “Theory Methods Society”, which provides ample opportunities for collaboration and, potentially, research visits. Existing collaborations with applied researchers provide opportunities for proofs-of-concept of your newly developed methods with real data, and – time permitting – additional publications, thus improving your resumé and network. 

Your responsibilities  

• Conducting empirical and methodological research
• Developing user-friendly open source research software (in R and, optionally, Python)
• Preparing scientific articles for publication in international journals (ideally open access), present key findings at national and international scientific conferences, and write a dissertation that connects your scientific articles.
• Active participation in the Department of Methodology and Statistics, Theory Methods Society, and optionally, your choice of other professional organizations, including the Tilburg Meta-Research Center, Open Science Community, Paul Meehl Graduate School, and the Interuniversity Graduat
• School of Psychometrics and Sociometrics (IOPS).
• Participating in collaborations with applied researchers in the areas of (mental) healthcare, climate science, adolescents’ emotional development and substance (ab)use, cooperation, and morality, or new collaborations established based on your interests.
• Contributing to education and supervision (e.g. supervising bachelor’s theses and research skills groups; not more than 10% of your time will be devoted)

We are looking for a PhD candidate with a strong background in machine learning, data science, or applied/mathematical statistics and interest in philosophy of science. Interdisciplinary candidates, especially with strong quantitative skills and a background in social science or philosophy of science, can also apply.

Other requirements include:

• A (nearly) completed (research) master’s thesis which, preferably, involves machine learning, a simulation study, and/or pertains to theory development.
• Programming skills in R, Python, or C++ 
• Research skills and data analytical abilities.
• Communication and cooperation skills and the willingness to work in a team.
• Project management and organization skills.
• Interest in open science and team science.
• Proficiency in English, including academic writing.
• Interest in providing small-scale education, such as teaching working groups or bachelor thesis supervision.

Tilburg University offers excellent benefits in a pleasant working environment: 

• A position based on 1.0 fte (40 hours per week). 
• A salary of minimum €2.901 and maximum €3.707 gross per month for full-time employment, based on UFO profile PhD and salary scale PhD. Tilburg University uses a neutral remuneration system based on relevant work experience. 
• This is a vacancy for for a PhD in accordance with Article 2.3 paragraph 8 sub b CLA DU. You will initially be given a temporary contract for the duration of 12 months.
• Vacation pay of 8% and a year-end bonus of 8.3%. 
• Over 8 weeks of vacation leave. 
• The opportunity to work partly on campus and partly from home with a home office allowance of €2 per day.
• Reimbursement for sustainable commuting: walking, cycling, and public transport. 
• A monthly internet allowance of €25.
• An options model in which you exchange benefits for things such as additional leave, more pension, a bicycle or personal training at our Sports Center. 
• A moving allowance (subject to conditions). 
• Employees from abroad may be eligible for a tax-free allowance for extraterritorial expenses equal to 30% of taxable salary. 
• A pension with ABP; the largest Dutch pension fund.
• Training in personal development, career development, leadership, education, and research. Or a language course at our Language Center. 
• A work culture in which we embrace differences, everyone is welcome and given equal opportunities. 
• A vibrant campus in green surroundings that is easily accessible by public transport. 

For more information, see our website nd the CLA Dutch Universities. 

Tilburg University is an academic, inclusive, and engaged community. Together with nearly 3,000 employees, we are committed to broad prosperity, sustainably, and inclusion. For current and future generations. We develop and share knowledge for the requirements of people and our society. This is how we contribute to solving complex social issues and help society move forward.

We educate our 19,500 students of 110 nationalities to become responsible leaders with knowledge, skills, and character. With our education and research for broad prosperity, we exceedingly focus on themes such as mental and preventive care, an inclusive labor market, the energy transition, and digitalization.

About Tilburg School of Social and Behavioral sciences
Tilburg School of Social and Behavioral Sciences (TSB) is one of the five faculties of Tilburg University. The teaching and research of the Tilburg School of Social and Behavioral Sciences are organized around the themes of “Adaptive societies, organizations, and workers”, “Healthy life span”, and “Personalized prevention and care”. The School’s inspiring working environment challenges its workers to realize their ambitions, involvement and cooperation are essential to achieve this.  
Tilburg School of Social and Behavioral Sciences | Tilburg University

Department Methodology and Statistics
The Department of Methodology and Statistics is responsible for education and research in methodology and statistics for the social and behavioral sciences.
Methodology and statistics play an essential role in all subfields of the social and behavioral sciences, and related fields. At the Department of Methodology and Statistics we do research on and teach about quantitative and qualitative methods that researchers need in order to answer challenging research questions, come up with strong research designs, critically apply statistical analyses, and avoid bias when interpreting research findings. Within the department, there is a strong focus on developing novel statistical and methodological techniques to tackle complex problems in the social and behavioral sciences.
Department Methodology and Statistics | Tilburg University

Information and application 
Would you like to know more before applying? Feel free to contact to email Caspar van Lissa via c.j.vanlissa@tilburguniversity.edu.

We kindly invite you to apply before July 1st, 2025; this can only be done online. Address your cover letter to dr. Caspar van Lissa. 

Important: Reducing hiring bias
To reduce hiring bias, the first selection will be “blind”. We ask you to anonymize your motivation letter and CV as much as possible. Please identify yourself by your initials, and remove information that could be subject to hiring bias (including your name, sex/gender, background, profile picture). An independent party will ensure that the committee views only anonymized applications. The interview stage will not be anonymous.

Your application should include:

1. Maximum 1000 word letter of motivation, explaining 1) why you are interested in the position, describing 2) how the position connects to your prior education and (school/work) experience, describing 3) the direction you would like to take the project in and 4) the ways in which you would most enjoy contributing to the team.
2. Curriculum vitae (education/work experience, skills, etc.)
3. List of grades (ideally: official grade transcript)
4. Optional: A sample of your academic writing (e.g. bachelor/master thesis draft, written assignment).
5. Optional: A sample of code you have written