Postdoctoral Researcher (E13 TVöD Bund, 100%) in Computational Social Science with a Focus on

Job description \ Develop methodologies for the empirical analysis of gender-based disinformation across multiple online platforms, potentially with the help of LLMs. \ Collect, process and synthesize online data consisting of text-based and audiovisual content. \ Contribute to developing keyword dictionaries and computational resources for corpus analysis. \ Contribute to conducting computational and qualitative content analyses of gender-based disinformation campaigns. \ Apply embedding-based topic modelling and other state-of-the-art NLP methods. \ Conduct social network analyses of interaction networks and user-driven amplification processes. \ Develop and validate coding schemes for multimodal and visual data analysis. \ Support the preparation of scientific publications, project reports, presentations and dissemination activities. \ Collaborate closely with project partners and contribute to the further development of the project’s computational research infrastructure and datasets. Your profile \ A completed or nearly completed PhD in computational social science, communication science, political science or a related discipline. \ Familiarity with social science theories, and a strong interest in answering social science research questions with a mixture of computational and social science methods. \ Demonstrated expertise in computational social science methods, including experience in computational and qualitative analysis of visual and multimodal data (e.g., NLP, topic modelling, embeddings, machine learning). \ Proven experience in statistical analysis and quantitative research methods with programming skills in Python and/or R. \ Excellent publication record or demonstrated potential, as well as excellent scientific writing skills in English. \ Ability to work independently as well as in close collaboration with colleagues, contributing effectively within an interdisciplinary research team. \ Experience working with LLM APIs is desirable. \ Experience with social network analysis and digital trace data is an advantage. \ Experience scraping and analyzing data from online platforms is an advantage. Your opportunity \ Exciting tasks: Work in a committed, innovative and scientific environment. \ Optimal conditions: Compensation depending on qualifications up to EG 13 (TVöD Bund, Stufe depending on qualifications, check gross salary estimate here: https://oeffentlicher-dienst.info/tvoed/bund/), including annual bonus, company pension plan, and subsidy for the Deutschlandticket. \ Funding for data collection, processing and analysis software and international conference attendance. \ Work-life balance: We offer flexible working hours and the option of remote working on certain days per week (in consultation with team lead), 30 days of vacation per year (based on a 5-day week), plus paid time off on Christmas Eve and New Year's Eve. \ Central location: Work in the center of Berlin. \ Career development through a multitude of in-house events, training opportunities and cross-institutional networks. \ A young, enthusiastic, intercultural and interdisciplinary team that is happy to welcome new colleagues. Your application Severely disabled applicants with equal qualifications will be given preference. We value diversity and welcome all applications, regardless of gender, nationality, ethnic or social origin, religion, disability, age or sexual orientation. The Weizenbaum Institute expressly encourages women* and people with a migration background to apply. The application must include: \ Cover letter, describing your research interests, skills and your fit to the research project; \ CV; \ Complete record of your courses, including grades and an explanation of the grading system; \ The names and contact information of at least two academic references (please do not include the letters themselves); \ A link to/a copy of a written work product (e.g., academic publication) Please note that application documents should reflect your own qualifications, experiences, and motivation. Applications generated wholly or predominantly using artificial intelligence (AI) will not be considered. If you do not fit to all the criteria but nevertheless think that you could be a good fit to the project, we encourage you to apply. For questions about the post, please reach out to the project lead Dr. Elizaveta Kuznetsova (elizaveta.kuznetsova@weizenbaum-institut.de). Pre-application inquiries are explicitly encouraged. Please submit your application by 15 August 2026, via our applicant portal. If you have any technical questions about the application process, please feel free to contact our HR department Umut Erdogan (personal@weizenbaum-institut.de) at any time.