PhD Position (m/f/d) in the Everyday Media Lab

Subject to final approval as part of the interdisciplinary project ‘Human-Centered Agentic Science’, the Everyday Media Lab is offering a

PhD Position (m/f/d)

Part-time 75%, fixed term for three years (one year extension negotiable), starting January 2027 or later (the latest April 2027).

The Everyday Media Lab investigates (incidental) knowledge processes that occur when people engage with social media or communicative AI, whether in everyday life or in professional contexts. Human-Centered Agentic Science is an interdisciplinary project funded through the Innovation Fund Program of the Cluster of Excellence – Machine Learning for Science. The project is run jointly by researchers from different departments of the University of Tübingen (Prof. Dr. Carsten Eickhoff and Dr. Harrisen Scells (both Health NLP Lab); Prof. Dr. Christoph Bareither (Cultural Anthropology and Digital Anthropology)).

The successful candidate will work alongside three other PhD students (two from computer science and one from anthropology) on the question of how agentic AI can be integrated into the research process. The subproject Advancing Human-centered Agentic Science through Psychological Approaches at the IWM focuses on potential unintended effects of agentic science. These effects will be studied on three levels: researcher’s motivation, researcher’s reputation within the scientific community, and broader societal perceptions. The successful candidate will conduct surveys and experiments among scientists from various disciplines as well as members of the general public. Once prototypes have been developed within the first two subprojects, additional studies with test users will be carried out. The subprojects are tightly integrated and require interdisciplinary collaboration.

Your responsibilities will include designing, conducting, and analyzing empirical studies, presenting findings at national and international conferences, and publishing in peer-reviewed international journals. Participation in regular events organized by the Cluster of Excellence - Machine Learning for Science is expected. You will also be involved in the establishment/expansion and co-supervision of an interdisciplinary “Hub for Human-Centered Agentic Science,” in which activities in the field of agentic science within the Cluster of Excellence are consolidated and networked with other institutions. In addition, you will support the administrative management of the lab. Writing your doctoral thesis on a self-generated research question in one of the research areas of the lab is desired and explicitly supported.

Your profile:

• Above-average degree (Master's or equivalent) in psychology, cognition science or related disciplines

• Experience in the design, planning, conduction and analysis of quantitative empirical studies

• Interest in machine learning / agentic AI and working in interdisciplinary teams and contributing to a culture of shared learning

• Self-motivated and pro-active working style with an open and curious mindset

• Very good command of English; knowledge of German is an asset

We offer:

• An exciting and varied field of research with creative freedom in an interdisciplinary and internationally oriented research institute located in central Tuebingen (Germany)

• Work in an cooperative an enthousiastic team as well as a stimulating, international and interdisciplinary oriented research environment

• Remuneration based on the collective agreement for the public service in the federal states of Germany, including the social benefits customary in public service

• Employment, remuneration (pay group 13 TV-L) and social benefits, including company pension scheme and 6 weeks annual leave, are based on the collective agreement for the public service in the federal states of Germany (TV-L)

• Reconciliation of work and family life, family-friendly working hours, cost subsidy for pre-school childcare

• Mobile working option (hybrid), subsidy towards the Deutschlandticket as a job ticket, occupational health management (OHM)