Research Assistant (Praedoc) (m/f/d) with 65 %-part-time job limited up to 5 years Entgeltgruppe 13 TV-L FU Reference code: WiMi DIGIMETH 2023

The members of the new digital methods division develop, evaluate, and teach innovative digital and computational research methods. We use these methods to analyze public communication, primarily in the fields of political communication and health communication. We consult and cooperate with the divisions of the Institute for Media and Communication Studies to contribute our methodological expertise to various research projects. We embrace the Open Science principles in research and teaching.
The division is part of the Institute for Media and Communication Studies. The eleven divisions cover communication research in all its fields and methodological approaches. The Freie Universität and the research hub Berlin stand for excellent and international research and teaching.
As a founding member of the division, you have the opportunity to participate in developing our research and teaching profile. Funding is available for data collection, computational services, advanced training, and conference participation. The part-time position of 65% translates to about 26 hours per week. The starting salary is currently about 2.800€ gross per month (collective agreement TVL-E13, level 1).

Job description:

– Participation in the research and teaching activities of the digital methods division; some administrative tasks
– The pursuit of a Ph.D. is encouraged

Requirements:

– Completed academic degree (Magister, Diplom, Master) in communication science, an adjacent social science (e.g., political science, sociology, psychology, economics), computer linguistics, statistics, data science, or computer science

Desirable:

* First experiences with conducting an empirical research project, demonstrated by an excerpt of a degree paper or seminar paper (in English or German)

* Fluency in German or English (spoken and written)
* Ability to work with R or Python; or fluency in another data analysis software and willingness to learn R or Python
* Excellent knowledge of empirical communication research or social science research methods, ideally computational methods

For further information please contact Prof. Dr. Marko Bachl (marko.bachl@fu-berlin.de).