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 young professionals develop the skills and judgment needed to work meaningfully and effectively with generative AI in everyday professional contexts. It will move beyond questions of whether and how AI is used to explore how people learn to work alongside it, divide tasks and responsibilities, assess its contributions, and retain control over decisions and outcomes.
At the center of the project will be the concept of co-agency: how human and AI abilities come together in professional work and how this relationship develops over time. The project will focus on areas such as augmentation, calibration and error detection, responsible disclosure, adaptation to AI behavior, and the ability to recognize when human judgment should take precedence. It will also examine how professionals develop an understanding of what AI can and cannot do, and how this shapes trust, autonomy, and decision-making.
Taking an interdisciplinary and participatory approach, the project will investigate how these capabilities differ across professional roles, sectors, and levels of experience, and how they are shaped by individual characteristics and workplace environments. It will also consider their implications for motivation, autonomy, and well-being. The research will likely combine self-report measures, scenario-based tasks, behavioral experiments, and observational approaches to capture both how people understand their collaboration with AI and how they work with it in practice.
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.
At TUM, this doctoral project will be supervised by Prof. Sandra Cortesi.
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.
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, Prof. Urs Gasser, Prof. Christoph Lutz, and Prof. Gemma Newlands.
Applicants of any nationality can apply. Because the position is funded by the EU's Marie Skłodowska-Curie Actions, a few rules apply:
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 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.
Please submit your application through the online application form by November 1. Your application should include:
Questions? 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 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.
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 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.
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