Postdoc (m/f/d) in the ERC project “Algorithmic Governance – A Public Perspective” (AGAPP) (E13[...]

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About Us

The Munich School of Politics and Public Policy (HfP), affiliated to the Technical University of Munich (TUM), deals with the multifaceted interactions between politics, society, business and technology in research, teaching and practice. It was established by the Bavarian State Parliament based on a separate law.

The Professorship “Algorithmic Governance and Public Policy” focuses on the policy, ethical, and societal implications of algorithmic decision‑making across public and private domains. Our team combines cutting‑edge computational techniques with traditional social science methods and is equally interested in methodological innovation and in the broader consequences of automation for democratic institutions. Prof. Gritsenko is a political scientist who has carried out qualitative, quantitative, and experimental research on topics of policy and governance, including energy, environment, and digital transformation.

This position is part of an ERC Starting Grant awarded to Associate Professor Daria Gritsenko (Principal Investigator) for a project examining how perceptions of legitimacy are shaped and changed in the minds of individuals in the context of algorithmic governance. The AGAPP project integrates methods from cognitive science with focus groups and survey experiments to explore how people evaluate the legitimacy of algorithmic governance in the context of migration policy. The project team collects quantitative and qualitative data to study how people use heuristics to judge legitimacy of algorithmic systems of rule, with the view to building theory of legitimacy for the digital age.

Responsibilities

How do individuals evaluate legitimacy of algorithmic governance? The main task of the appointed researcher is to contribute to answering this research question by designing, coordinating and conducting empirical research on the use of heuristics in cognition of algorithmic legitimacy. Working closely with the Principal Investigator, the post‑doctoral fellow will play a pivotal role in project implementation individually and jointly with other team members. The appointee will help to develop an in‑depth understanding of cognitive processes in the context of legitimacy and translate it into concepts that can be operationalised in empirical, especially experimental, studies, and by using focus groups, interviews and think‑aloud methods. Other main tasks include writing up joint peer‑reviewed publications on methodological and comparative aspects of the project, working on individual peer‑reviewed articles, and actively participating in online and onsite research activities of the group. The appointed researcher will also contribute up to 10 % of their annual working time to teaching and administrative tasks at the Professorship “Algorithmic Governance and Public Policy”. It is possible to complete the teaching and administrative tasks in English.

Qualifications

An appointee to the position must hold a doctoral degree in social or behavioural sciences (incl. human‑computer interactions with relevant experience). Applicants must demonstrate experience in experimental work with human participants; possess versatile methodological skills (ideally both quantitative and qualitative); have the ability to work independently and collaboratively in research teams; and have an excellent command of written and spoken English. The default assumption is that the doctoral degree requirement must be met by the beginning of the employment. The chosen applicant is expected to reside in Germany while employed by the TUM.

Essential qualities and attributes

The ideal candidate would have a proven track‑record of creating and deploying mixed‑method research designs to study human decision‑making. Successful applicants will demonstrate excellent methodological and academic writing skills, experience with data management and confidence in data analysis (R, STATA, etc.). While experience in experimental work with human participants is a must (lab, field, experimental UI/UX, etc.), preference will be given to applicants who can also demonstrate experience in qualitative research (such as interviews, focus group design and analysis). Strong organisational skills are required in order to plan and conduct fieldwork in two countries (UK and Singapore). Familiarity with ecological rationality framework is a plus. As the post‑doctoral researcher will be working in a team with other researchers, including PhD students, it is essential that applicants demonstrate good communication skills.

What we offer

The successful candidate will become part of a vibrant research environment of the School of Social Sciences and Technology (SOT) at TUM. This three‑year full‑time position provides excellent opportunities for intellectual development, support for additional training, help to build an outstanding publishing record, and opportunities to teach and (co)‑supervise MA students. The project offers funding for conferences, fieldwork, and opportunities for developing a strong academic network. We support Open Science and Open Access publications. The salary is based on your qualifications and personal suitability in accordance with TV‑L (salary scale E13). Applicants of any gender, nationality and cultural background are welcomed.

Further information

Further information about the position and the research project may be obtained from Dr. Daria Gritsenko, daria.gritsenko(at)tum.de

How to apply

Applicants are requested to enclose with their applications the following documents in English:

• Attachment 1) A curriculum vitae that includes the names, positions and contact details of two referees.
• Attachment 2) A statement (max. 600 words) outlining how the applicant would contribute to the AGAPP project.
• Attachment 3) A numbered list of publications on which the applicant has marked in bold their one to three key publications to be considered during the review.
• Attachment 4) An outline (max. 300 words) of the applicant’s methodological skills (quantitative, qualitative, experimental), experience with software, fieldwork experience, etc., with reference to publications (Attachment‑3).

Please send these documents by e‑mail in a single PDF document to by February 6, 2026 at the latest.

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