Beschreibung
At the University of Göttingen -Public Law Foundation-, Niedersächsische Staats- und Universitätsbibliothek, there is a position as
Research Assistant (WHK) for Media Bias Analysis (all genders welcome)
to be filled. The starting date is as soon as possible. The position is limited to April 30, 2029.
The Chair of Scientific Information Analytics, headed by Prof. Dr. Bela Gipp (GippLab, https://gipplab.uni-goettingen.de), conducts research at the intersection of computer science, data science,...
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At the University of Göttingen -Public Law Foundation-, Niedersächsische Staats- und Universitätsbibliothek, there is a position as
Research Assistant (WHK) for Media Bias Analysis (all genders welcome)
to be filled. The starting date is as soon as possible. The position is limited to April 30, 2029.
The Chair of Scientific Information Analytics, headed by Prof. Dr. Bela Gipp (GippLab, https://gipplab.uni-goettingen.de), conducts research at the intersection of computer science, data science, and information science. Natural language processing (NLP) based on Large Language Models (LLM) is a particular research focus of the chair.
GippLab is seeking one research assistant (WHK) position to support the research project BARI: Bias Analysis Research Infrastructure. The working hours are between 46 and 86 hours a month. Fewer hours are possible for recipients of a stipend.
Short Project Description: Media bias in online news impacts public opinion and decision-making. While NLP methods allow us to classify and analyze content, there are no systems designed for expert analysis, and we lack an understanding of how to effectively design systems for communicating media bias insights. The BARI project proposes to design, develop, and test a scalable platform for bias analysis. The platform combines machine learning, large language models, and human-in-the-loop feedback to establish a new community-driven standard for media bias research. It enables users and researchers to conduct in-depth analyses of bias and participate in discussions about the complex topic of media bias. The goal is to help users gain a deeper understanding of how media bias manifests and affects individuals and the public, ultimately increasing awareness and mitigating its negative effects. For this purpose, we need a motivated scientific assistant with a background in human-computer interaction, computer science, and psychology, as well as UI/UX design expertise and experience conducting scientific user studies.
This project is a joint effort between the University of Göttingen (UGoe), the Göttingen State and University Library (SUB), and the National Institute of Informatics, Tokyo (NII Japan). Our multidisciplinary team brings together expertise in computer science, data science, social science, and media bias analysis. Our combined knowledge, skillset, and resources will enable us to design, develop, and implement BARI, conduct rigorous user studies, and establish pathways for a media bias discussion community in research and beyond.
Your Tasks:
Coordinating the creation of a data set (approx. 5 months)
Assist in structuring and organizing the work of the team
Supporting the development of classifiers and platform components
Designing and running data quality pipelines and measurement frameworks
Organizing workshops for the team and external stakeholders
Collecting and integrating community feedback
Collaborating with an interdisciplinary team of subject matter experts, data specialists, and project partners
Collaborating with international partners
Engaging with a multidisciplinary community of researchers and industry professionals
Supporting bachelor's and master's students working on related projects
This role requires regular on-site presence in Göttingen; remote work is possible to a limited extent.
Your Profile:
A master's degree with a grade of very good (or equivalent) in mathematics, data science, computer science, or a related discipline
Strong hands-on experience in media bias research
Strong skills in mathematical modeling and implementation
Understanding of NLP methods and their application to text analysis
Professional fluency (C1) in German and English, both written and spoken
Communicative and teamwork-oriented mindset
Intrinsic motivation to work on a societally relevant topic
We offer:
Involvement in an international network of researchers in computer science, journalism, psychology, and linguistics.
Provision of a strong platform for collaboration, feedback, and career development, with opportunities to co-author publications, co-organize international workshops, and connect to leading researchers and institutions worldwide.
Access to high-performance computing (GPU clusters), infrastructure, and interdisciplinary expertise.
Travel funding for conferences, project meetings, and exchange visits.
The University of Göttingen is an equal opportunities employer and places particular emphasis on fostering career opportunities for women. Qualified women are therefore strongly encouraged to apply in fields in which they are underrepresented. The university has committed itself to being a family-friendly institution and supports their employees in balancing work and family life. The University is particularly committed to the professional participation of severely disabled employees and therefore welcomes applications from severely disabled people. In the case of equal qualifications, applications from people with severe disabilities will be given preference. A disability or equality is to be included in the application in order to protect the interests of the applicant.
If you have any questions regarding the advertised position, please contact Dr. Norman Meuschke (meuschke@uni-goettingen.de).
Please submit your application, including all relevant documents combined into a single PDF file, by March 12 2026 via email to Dr. Norman Meuschke (meuschke@uni-goettingen.de).
Please note:
With submission of your application, you accept the processing of your applicant data in terms of data-protection law. Further information on the legal basis and data usage is provided in the https://uni-goettingen.de/GDPR