PhD Position in Empirical Economics & Data Science (Causal AI) at Technical University of Munich, Campus Heilbronn Technical University of Munich in Germany

The Professorchip of Empirical Economics & Data Science at the Technical University of Munich (TUM), Campus Heilbronn, invites applications for a PhD position starting as soon as possible for an initial duration of four years. This opportunity is part of the Heilbronn Data Science Center and the TUM School of Management, offering a vibrant interdisciplinary research environment at the intersection of econometrics, innovation policy, and technology management.

The research focus centers on causal data science, with particular emphasis on causal AI—addressing fairness, reliability, and transparency in economic and managerial decision-making. Applicants with interests or backgrounds in causal inference, empirical methods, and the societal and managerial implications of AI are especially encouraged to apply. The group combines rigorous empirical methods with interdisciplinary perspectives to understand how advanced technologies can be responsibly deployed in business and society.

TUM Campus Heilbronn is part of the renowned Technical University of Munich, recognized for excellence in research and teaching, interdisciplinarity, and talent development. The TUM School of Management is the first management school at a technical university in Germany to receive Triple Crown accreditation (AACSB, AMBA, EQUIS), a distinction held by only around 1% of business schools worldwide. The Professorchip is affiliated with the Department of Economics and Policy and the Heilbronn Data Science Center, which is dedicated to interdisciplinary research in data science and artificial intelligence, focusing on business and societal applications.

PhD candidates will contribute to high-quality publications in leading international journals, present research at international conferences, teach and develop courses within the Bachelor’s and Master’s programs, supervise theses, collaborate with academic and industry partners, and support the organization of academic conferences and administrative tasks.

Applicants must hold a Master’s degree in Economics, Data Science, Management, or a related field. A strong background in quantitative methods and statistics is required; experience in causal inference and econometrics is a plus. Strong programming skills in Python, R, or comparable languages are expected. Ability to conduct independent, rigorous research and experience with large datasets are advantageous. Excellent communication skills in English (written and spoken), as well as strong organizational and teamwork skills, are required.

The position offers a highly interdisciplinary and collaborative research environment, close integration into the Heilbronn Data Science Center, opportunities to publish and present at top international venues, access to a global academic and industry network, a diverse and inclusive workplace, and structured training and professional development opportunities. PhD positions are initially funded at 75% (TV-L E13), with the possibility of increasing to 100%. The position is suitable for applicants with disabilities, who will be given preference in cases of equal suitability, aptitude, and professional performance. TUM is committed to increasing the proportion of women in its workforce and explicitly encourages applications from qualified women.

Applications should be submitted by May 30, 2026, as a single PDF document via email to [email protected] (contact person: Ms. Elke Kröber) with the subject “PhD Empirical Economics and Data Science.” Applications may also be sent by post to TUM School of Management, UDSM, Elke Kröber, Bildungscampus 2, 74076 Heilbronn. Please ensure all documents are copies, as originals will not be returned. Applicants should review TUM’s data protection information in accordance with GDPR before submitting their application.