Doctoral Candidate for MSCA Doctoral Network REGULAIRE, DC13: Participation, Evidence and Regulatory Memory

Open PhD Position for MSCA Doctoral Network REGULAIRE

Doctoral Candidate for MSCA Doctoral Network REGULAIRE, DC13: Participation, Evidence and Regulatory Memory

25.09.2026, Wissenschaftliches Personal
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Are you curious why public institutions keep relearning the same lessons, and how to fix that? TUM is hiring a doctoral researcher for REGULAIRE, a Marie Skłodowska-Curie Actions (MSCA) Doctoral Network exploring how regulation learns in the governance of emerging technologies. This is a paid, three-year employment contract, not a scholarship, with full training, international mobility and close supervision.

Position details

• Employer: Technical University of Munich, School of Social Sciences and Technology. You must be willing to enroll in a doctoral programme at the TUM School of Social Sciences and Technology.
• Contract: Full-time employment contract (40 hours per week) for 36 months, with social security, health insurance and pension contributions
• Salary: A gross monthly salary of approximately €3,800, before taxes and social security contributions (remuneration in accordance with the MSCA Grant Agreement), includes the MSCA mobility allowance and, if you have a family, the MSCA family allowance is available. See “What we offer” below.
• Location: On site in Munich, Germany, as required by the MSCA programme; with travel for network events. The position requires full-time commitment with a physical presence at the recruiting institution. Teleworking is not permitted.
• Language: The working language is English. German is not required.
• Expected start: 01.02.2027, or upon agreement
• Application deadline: 31 October 00:00 CET

About REGULAIRE

REGULAIRE (Regulatory Learning for the Governance of Transformative Technologies) is a Marie Skłodowska-Curie Actions Doctoral Network bringing together 15 doctoral candidates at ten European universities to study how regulation can learn to govern transformative technologies such as AI, quantum computing and neurotechnology. Its projects examine how regulators sense emerging problems early, how balanced interventions encourage learning without overcorrection or underreaction, how such interventions alter institutional capacities, and how feedback can be institutionalised so that insights travel across organisations and jurisdictions. Across the network, regulatory learning means treating regulation as a learning architecture that generates, tests and refines knowledge about what works, rather than as one-off rulemaking.

As part of the network, you'll join an international cohort and be supervised across institutions. You will take part in three residential summer schools, methods workshops, monthly paper development seminars and joint work with regulators, standardisation bodies, and international organisations. The network is coordinated by Prof. Urs Gasser (Chair for Public Policy, Governance and Innovative Technology) and Prof. Sandra Cortesi (Professorship for Participation and Diversity in Digital Societies) at the Technical University of Munich (TUM).

The doctoral project

Public institutions gather evidence from research, practice and the people affected by their decisions. Yet these insights do not always reach those making policy, and lessons can disappear when personnel change or initiatives end. This doctoral project examines how institutions can bring different forms of knowledge into regulatory learning and retain them across time, organisations and jurisdictions. You will study how public agencies and other governance actors gather, interpret, document and reuse evidence, with particular attention to participation by young people and other groups whose experiences may otherwise receive too little attention. The project may examine participatory research, consultation, reporting and feedback practices, asking whose knowledge becomes part of the institutional record and how it informs later decisions.

Concretely, the project will develop a framework for understanding where evidence is lost or overlooked across regulatory cycles and investigate practices that help institutions preserve and share it. Depending on the research approach, it may combine case studies, interviews, participatory methods, document analysis or other suitable methods. It may also contribute insights or practical approaches to the REGULAIRE Observatory. Within the network, the project contributes to Work Package 5 by examining how feedback from different sources can become a durable part of institutional learning.

This project is a good fit if you are interested in technology governance, participatory research, youth and other affected communities, public policy, institutional learning, or how evidence informs decisions. We welcome applicants from different disciplinary backgrounds.

At TUM, this doctoral project will be supervised by Prof. Sandra Cortesi.

What you will do

• Shape the research questions and design together with the supervision team, and prepare the ethics, data-management, and open-science materials.
• Collect, manage, and analyse data, for example through analysis of public records and freedom-of-information documents, mapping of governance processes, and interviews or workshops with practitioners.
• Write a doctoral thesis and related publications within the doctoral programme and the REGULAIRE plan.
• Take part in local and network-wide training and cohort activities, including three residential summer schools and monthly paper development seminars, and share your work with researchers and practitioners.
• Complete a three-month secondment with a non-academic partner.
• Contribute to research integrity, equality and diversity, open science, and FAIR data practices.

What we are looking for

Essential

• A Master's degree, or an equivalent qualification that gives you access to doctoral studies, completed by the start date. Relevant fields include law, political science, science and technology studies, psychology, communication science, information and library science, and other social science or interdisciplinary fields.
• A genuine interest in how public institutions create, document and reuse knowledge.
• Professional working proficiency in English, spoken and written. Non-native speakers are very welcome.
• Willingness to travel for the secondment and network activities.
• Eligibility under the MSCA rules (see “Am I eligible?” below), and willingness to enrol in the doctoral programme at the TUM School of Social Sciences and Technology.

Helpful, but not required

• Experience with document or archival analysis, including freedom-of-information (FOI) requests.
• Experience mapping governance or organisational processes, or developing protocols, guidelines or templates.
• Work experience in government, regulatory agencies, standards bodies, libraries, archives, or records management.
• Familiarity with qualitative or mixed methods.

Don't meet every point? Please apply anyway. We know that strong candidates often hold back unless they match every item on a list. If this project excites you and you meet the essential criteria, we would like to hear from you. Non-linear career paths, career breaks and experience outside academia are all valued.

Supervision, training and mobility

You'll be supervised by Prof. Sandra Cortesi (TUM, primary supervisor). You'll meet your primary supervisor at least once a month and the full team at least four times a year. Your progress and training are recorded in your Career Development Plan.

Network-wide training includes three residential summer schools (regulatory learning and foresight at TUM; methods and analytics at BI Norwegian Business School; academic writing and impact at the University of St. Gallen), monthly paper development seminars, and annual network reviews aligned with major community events. Over the project, you'll earn at least 20 ECTS through local and network-wide training, including at least 10 ECTS from network-wide activities.

Am I eligible?

Applicants of any nationality can apply. Because the position is funded by the EU's Marie Skłodowska-Curie Actions, a few rules apply:

You must be able to enrol in the TUM doctoral programme in time.

You must be “mobile”. In the 36 months before your start date, you must not have lived, worked or studied mainly in Germany for more than 12 months. Holidays, compulsory national service and time spent in a procedure to obtain refugee status do not count.

You must not already hold a PhD. If you have defended a doctoral thesis but not yet formally received the degree, you are also not eligible.

Example: If you start on 1 January 2027, look back to 1 January 2024. If you spent more than 12 months of that period living, working or studying mainly in Germany, you are not eligible for this position. You may still be eligible for REGULAIRE positions in other countries, so please check the network's other openings.

Formal wording: Applicants may be of any nationality. To be eligible for MSCA funding, the selected candidate must, on the first day of MSCA employment: (i) not hold a doctoral degree; candidates who have successfully defended a doctoral thesis but have not yet formally received the degree are not eligible; (ii) comply with the MSCA mobility rule, meaning they must not have resided or carried out their main activity (work, studies, etc.) in Germany for more than 12 months during the 36 months immediately preceding that date, excluding compulsory national service, short stays such as holidays, and time spent in a procedure for obtaining refugee status under the Geneva Convention; and (iii) be enrolled in, or meet the conditions required for timely enrolment in, the doctoral programme leading to the degree specified in this notice. The appointment is conditional on documentary verification of these conditions and fulfilment of the host institution's doctoral admission requirements.

How to apply

Please submit your application through the online application form by 31 October 00:00 CET. Your application should include:

• A CV (no photo, date of birth or marital status needed).
• Copies of your degree certificates and transcripts. English translations are fine if the originals are in another language; certified copies are only needed if you are offered the position.
• A short research proposal of no more than 2 pages, explaining how you would approach this project, what interests you about it and what you would bring to it. We are not looking for a finished research design; we want to see how you think.
• Contact details for two referees. Letters requested only from shortlisted candidates.

Additional Information

Questions?

We're happy to answer questions about the project, eligibility or life in Munich. Please contact Prof. Urs Gasser (urs.gasser@tum.de) or Prof. Sandra Cortesi (sandra.cortesi@tum.de).

Equal Opportunity

We want REGULAIRE to reflect the diversity of the societies that regulation serves. We welcome applications from people of all nationalities, genders, ethnic and social backgrounds, ages, religions or beliefs, sexual orientations and abilities, and we particularly encourage applications from groups that are underrepresented in academic research, including first-generation university graduates.

The position is suitable for disabled persons. Disabled applicants will be given preference in case of generally equivalent suitability, aptitude and professional performance.

Data Protection Information:

When you apply for a position with the Technical University of Munich (TUM), you are submitting personal information. With regard to personal information, please take note of the Datenschutzhinweise gemäß Art.13 Datenschutz-Grundverordnung (DSGVO) zur Erhebung und Verarbeitung von personenbezogenen Daten im Rahmen Ihrer Bewerbung (data protection information on collecting and processing personal data contained in your application in accordance with Art. 13 of the General Data Protection Regulation (GDPR)). By submitting your application, you confirm that you have acknowledged the above data protection information of TUM.

Die Stelle ist für die Besetzung mit schwerbehinderten Menschen geeignet. Schwerbehinderte Bewerberinnen und Bewerber werden bei ansonsten im wesentlichen gleicher Eignung, Befähigung und fachlicher Leistung bevorzugt eingestellt.

Hinweis zum Datenschutz:
Im Rahmen Ihrer Bewerbung um eine Stelle an der Technischen Universität München (TUM) übermitteln Sie personenbezogene Daten. Beachten Sie bitte hierzu unsere Datenschutzhinweise gemäß Art. 13 Datenschutz-Grundverordnung (DSGVO) zur Erhebung und Verarbeitung von personenbezogenen Daten im Rahmen Ihrer Bewerbung. Durch die Übermittlung Ihrer Bewerbung bestätigen Sie, dass Sie die Datenschutzhinweise der TUM zur Kenntnis genommen haben.

Kontakt: urs.gasser@tum.de

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