Doctoral Candidate for MSCA Doctoral Network EMANAIRE, DC11: Human-Machine Communication in Hybrid Knowledge-Intensive Work

Offer Description

Doctoral Candidate for MSCA Doctoral Network EMANAIRE, DC11: Human-Machine Communication in Hybrid Knowledge-Intensive Work

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.

The position comes with a full-time employment contract, international training and mobility, a six-month intersectoral secondment, and close supervision within an interdisciplinary European research network.

POSITION DETAILS

• Employer: Technical University of Munich, School of Medicine and Health and School of Social Sciences and Technology. You must be willing to enroll in a doctoral program at either the TUM School of Medicine and Health or 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. Approximately 25% of the position will be dedicated to teaching and other career-development activities.
• Salary: A gross monthly salary of approximately €3,800 before taxes and social security contributions, in accordance with the MSCA Grant Agreement. This amount includes the MSCA mobility allowance. An additional family allowance may be available to eligible candidates.
• Location: On site in Munich, Germany, as required by the MSCA program; 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: 01.01.2027, or upon agreement
• Application deadline: 07.11.2026

ABOUT EMANAIRE

EMANAIRE: https://emanaire.eu/ 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.

THE DOCTORAL PROJECT

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.

At TUM, this doctoral project will be supervised by Prof. Sandra Cortesi (sandra.cortesi@tum.de).

YOUR WORK

• Examine how professionals in knowledge-intensive fields interact and communicate with generative AI in their day-to-day work.
• Investigate how workers shape AI outputs through practices such as prompting, editing, refining, correcting, and providing context, and how AI in turn shapes attention, decisions, and workflows.
• Study how human–AI interaction develops over time, including how professionals adapt their communication practices, redistribute cognitive effort, and negotiate changing boundaries between human and AI contributions.
• Examine the often overlooked work required to make human–AI interaction function in practice, including evaluating outputs, correcting errors, maintaining context and consistency, and deciding when to intervene or retain control.
• Develop an evidence-based framework for identifying and comparing different patterns of human–AI interaction, including when these patterns remain stable, break down, or shift across tasks, professions, and over time.
• Translate findings into implications for the design and governance of AI systems that are transparent, fair, and accountable to the people working with them.
• Develop and refine the research questions and study design together with the supervisory team, using qualitative, quantitative, or mixed methods appropriate to the research questions.
• Prepare ethics, data management, and open science materials and conduct the empirical research.
• Contribute to teaching at TUM, including the preparation and delivery of courses and supervision or support of student work.
• Complete a doctoral thesis and related research outputs within the TUM doctoral program and the EMANAIRE network.
• Take part in local and network-wide training, cohort activities, reviews, dissemination, and engagement with organizations beyond academia.
• Undertake the planned six-month intersectoral secondment and academic mobility visit.
• Contribute to research integrity, equality, responsible AI, 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, psychology, communication, media studies, human-computer interaction, information systems, sociology, management, organizational behavior, human resource management, law and technology, science and technology studies, political science, or related social-science and interdisciplinary fields.
• 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 enroll in the doctoral program at either the TUM School of Medicine and Health or the TUM School of Social Sciences and Technology.

Helpful, but not required

• Interest in human–AI communication, human–computer interaction, digital technologies at work, knowledge work, professional practices, or related topics.
• Strong qualitative, quantitative, or mixed-methods skills and an interest in studying how human–AI interaction unfolds in real-world professional contexts.
• Experience with interviews, observational or ethnographic approaches, surveys, experiments, interaction or trace data, or other relevant empirical methods would be advantageous.
• Interest in how technologies shape communication, professional practice, expertise, decision-making, and the organization of work.
• Interest in interdisciplinary and participatory research and in working across different professional or organizational contexts.
• Strong academic writing skills and motivation to publish in international peer-reviewed journals.
• Interest in teaching and working with students in an interdisciplinary university environment.

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

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).

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 not already hold a PhD. If you have defended a doctoral thesis but not yet formally received the degree, you are also not eligible.
• 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. 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 EMANAIRE positions in other countries, so please check the network's other openings.
• You must be able to enroll in the TUM doctoral program in time.

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.

HOW TO APPLY

Please submit your application through the online application form by November 7. 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 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.

EQUAL OPPORTUNITY

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.

Where to apply

Website: https://emanaire.eu/

Requirements

• Research Field: Other
• Education Level: Master Degree or equivalent

Work Location(s)

• Number of offers available: 1
• Company/Institute: Technical University of Munich
• Country: Germany
• City: Munich
• Postal Code: 80333
• Street: Arcisstraße 21

Contact

• State/Province: Bavaria
• City: München
• Street: Arcisstraße 21
• Postal Code: 80333
• E-Mail: sandra.cortesi@tum.de