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The Technical University of Munich (TUM) invites applications for a fully funded 3-year doctoral researcher position within EMANAIRE, a Marie Skłodowska‑Curie Actions network. The position is on-site in Munich and requires enrollment in a TUM doctoral program. The project focuses on how professionals interact with generative AI in daily work and evolves with time.
The working language is English. Start date is 01.01.2027.
Academic staff
The Technical University of Munich (TUM) is recruiting a doctoral researcher for EMANAIRE (Empowering Human Agency in AI-Augmented Futures of Work), a Marie Skłodowska‑Curie Actions (MSCA) Doctoral Network studying how AI is changing work and human agency. This fully funded, three-year doctoral position will examine how professionals in knowledge-intensive fields interact and communicate with generative AI in their day-to-day work, and how these interactions evolve over time.
EMANAIRE is a Marie Skłodowska‑Curie Actions Doctoral Network bringing together 15 doctoral candidates at nine European universities to study how AI is changing work. Its projects examine what happens when generative and agentic AI enters leadership, everyday workflows, team communication, professional learning and career decisions. Across the network, human agency means the practical ability to understand AI‑supported decisions, exercise judgment, question outputs and shape how work is organized. Each researcher joins an international cohort, receives supervision across institutions and takes part in three residential schools, methods workshops, monthly research seminars and joint work with organizations beyond academia. Every project includes a planned six‑month intersectoral secondment.
This project will examine how workers in knowledge-intensive professions, such as law, academia, consulting, and journalism, engage with generative AI in their day-to-day work. Rather than treating AI as a static tool, the project will approach human‑AI interaction as an evolving communication process shaped by iteration, feedback, adaptation, and shifting control.
At the center of the project will be the two‑way relationship between professionals and AI. On one side, workers shape what AI produces through prompting, editing, refining, correcting, and customizing outputs. On the other, AI can shape workers by directing attention, suggesting courses of action, influencing decisions, and gradually changing how tasks and workflows are organized. The project will examine how these dynamics interact and how they develop as AI becomes more deeply embedded in professional practice.
A particular focus will be adaptation: how professionals adjust their communication practices, redistribute cognitive effort, and renegotiate their own role and expertise when working with AI. The project will also make visible the often overlooked work required to make human‑AI interaction function in practice, including the effort involved in providing context, evaluating outputs, correcting mistakes, maintaining consistency, and deciding when and how to intervene.
The research will seek to develop an evidence‑based framework for understanding different patterns of human‑AI interaction in professional settings, including when these patterns remain stable, break down, or change over time. It will also examine what these findings mean for the design and governance of AI systems that are transparent, fair, and accountable to the people working with them.
The specific research questions and design are not fixed in advance and will be developed together with the supervisory team. Applicants are encouraged to bring their own ideas to the project proposal that forms part of the application.
The selected candidate will receive close supervision and ongoing support from experienced research faculty. The main supervisor will be Prof. Sandra Cortesi. Depending on the focus of the project, co‑supervision may be provided by Prof. Christian Fieseler (BI), Prof. Urs Gasser (TUM), Prof. Christoph Lutz (BI), and Prof. Gemma Newlands (University of Zurich).
Applicants Of Any Nationality Can Apply. Because The Position Is Funded By The EU's Marie Skłodowska‑Curie Actions, a Few Rules Apply
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 enrollment in, the doctoral program 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.
We are very grateful for the strong interest in EMANAIRE and appreciate the time and thought that applicants put into their applications. As we are receiving a large number of applications and inquiries, we are unfortunately not able to respond to individual questions. We hope you understand, and kindly ask you to carefully review the information provided in the job posting and this application form.
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.
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.
Kontakt: sandra.cortesi@tum.de