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The Department of Communication in the Faculty of Education and Social Sciences at the University of Münster, Germany, invites applications for the following position, starting on 1 March 2027
Research Associate Wissenschaftliche*r Mitarbeiter*in (salary level E 13 TV-L)
for the interdisciplinary research project “Manipulation of the past: Far-right ideologies and the weaponization of history” (MAP), funded by the Volkswagen Foundation. We are offering a part-time position (65% FTE) on a three-year fixed-term contract.
Your tasks:
You will work within the international collaborative research project “Manipulation of the past”. The project examines how far-right actors in Spain, Italy, and Germany use historical narratives in digital communication and instrumentalize them for their political objectives. It focuses on the history of National Socialism, Italian Fascism, and the Franco regime, as well as the dissemination and algorithmic amplification of related content on platforms such as TikTok and YouTube. The advertised position in the subproject led by Prof. Dr. Thorsten Quandt focuses on empirical communication research. Using computational methods from digital communication research, the project examines how historical narratives emerge, evolve, and spread through digital media.
Your tasks will include:
- Contribute to the development of methods for the computational analysis of content on onlineplatforms
- Contribute to the development of data pipelines for collecting image and video data from onlineplatforms
- Conduct content analyses of social media data
- Present research findings at national and international conferences
- Publish research findings in international peer-reviewed journals, primarily in English
Our expectations:
- Master’s degree in Communication Science or a related social science discipline with a very goodor good final grade
- Demonstrated interest in the above research area and the development of social scienceresearch methods
- Interest in and ideally knowledge of social media research
- Good knowledge of empirical research methods
- Good knowledge of computational methods, particularly in the analysis of content data (text,images, and audio)
- Excellent written and spoken English
- Strong teamwork, communication, and organizational skills, as well as the ability to workindependently
- Due to the collaborative nature of the project and the research team, regular on-site presence inMünster is required
Advantages for you:
- The opportunity to work in a large, research-intensive team in the field of CommunicationScience and gain experience in a collaborative interdisciplinary research project
- Support with the development and realisation of your own research project within the OnlineCommunication Research Group
- Individual mentoring and opportunities for further training and professional development
- The opportunity to participate in international conferences and benefit from the group’sextensive network of academic collaborations. International mobility is actively supported andstrongly encouraged.
- A working environment characterized by appreciation, reliability, openness and mutual respect
The University of Münster strongly supports equal opportunity and diversity. We welcome all applicants regardless of sex, nationality, ethnic or social background, religion or worldview, disability, age, sexual orientation or gender identity. We are committed to creating family-friendly working conditions.
We actively encourage applications by women. Women with equivalent qualifications and academic achievements will be preferentially considered unless these are outweighed by reasons which necessitate the selection of another candidate.
If you have any questions, please contact Prof Thorsten Quandt (thorsten.quandt@uni-muenster.de).
Are you interested? Then we look forward to receiving your application by 2026-11-27 via email at:
University of Muenster
Department of Communication
Prof Thorsten Quandt
Reference number: Project MAP
kommunikationswissenschaft@uni-muenster.de
Your application can only be considered if submitted as a PDF file. Please note that we are unable to accept any other file formats.
Reference number: 2026_10_38
