Job description

The Collaborative Research Centre (CRC) 1342, "Global Dynamics of Social Policy," has been funded by the German Research Foundation (DFG) since 2018. The third phase represents the culmination of the 12-year research agenda. In Phase I, the worldwide introduction of social protection programs was mapped, and the Global Welfare State Information System (WeSIS) was established. Phase II documented the differences in the inclusiveness and scope of social policy benefits and integrated this information into WeSIS. In Phase III, based on this foundation, the socioeconomic effectiveness of social policy is being examined in terms of improving social conditions and promoting political integration.

The CRC is structured into two research areas. The six projects in Area A focus on the socioeconomic and political impacts of social policy in a global comparison. The six projects in Area B primarily investigate the political and socioeconomic consequences of social policy in selected countries or world regions. The Information Infrastructure Project (INF) provides a shared platform for data and methods.

This position is part of project Information Infrastructure (INF). With WeSIS, the INF Project provides a shared platform for data and methods which we will establish as a public resource. This requires new forms of user interactions, adding AI-based tools to improve user experience in a co-creative way. INF is concerned with the research data management for the CRC and aims to establish innovative Computational Social Science (CSS) methods. 

Tasks 

• Contribute collaboratively to the project’s empirical strategy by developing multimodal measures to detect protest and analyze social media behavior
• Supporting CSS services to all members of the CRC
• Contribution to research publications
• Develop and pursue your own PhD project (ideally related to the project themes)

Requirements

• An outstanding university degree (master's or university diploma) in the Social Sciences (political science, sociology, media studies or a comparable field) or in Computer Science with a specific focus on the Social Sciences
• Experiences with Data Science and methods of Computational Social Sciences; experience with NLP and quantitative text analysis are an asset
• Experience with Python and/or R
• Interest in interdisciplinary research project in the field of social policy research
• Willingness to engage in collaborative research
• High level of commitment and initiative, ability to work in a team, careful and reliable working style
• Excellent command of oral and written English#
• For degrees obtained outside the EU, please provide a German translation and an evaluation from the Central Office for Foreign Education (ZAB). Alternatively, you may submit a PDF extract from the ANABIN database on the recognition and evaluation of foreign educational qualifications

General Information

Open to unconventional approaches in research and teaching, the University of Bremen has retained its character as a place of short distances for people and ideas since its founding in 1971. With a broad spectrum of subjects, we combine exceptional performance and innovative potential. As an ambitious research university, we stand for research-based learning approaches and a pronounced interdisciplinary orientation. We actively pursue scientific cooperation in a spirit of global partnership. 

Today, around 23,000 people learn, teach, research, and work on our international campus. In research and teaching, administration and operations, we are strongly committed to the goals of sustainability, climate justice, and climate neutrality. Our Bremen spirit is expressed in the courage to try new things, in supportive cooperation, in respect and appreciation for each other. With our study and research profile and as part of the European YUFE network, we assume social responsibility in the region, in Europe, and in the world.

The university is family-friendly, diverse and sees itself as an international university. We therefore welcome all applicants regardless of gender, nationality, ethnic and social origin, religion/belief, disability, age, sexual orientation and identity.

As the University of Bremen intends to increase the proportion of female employees in science, women are particularly encouraged to apply. In the case of equal qualifications, women are given priority, unless reasons relating to the person of a competitor prevail.

Disabled applicants will be given priority if their professional and personal qualifications are essentially the same. 

For general questions about the personnel selection procedure, as well as questions regarding the content of the advertised position, please contact: hungerprotect me ?!uni-bremenprotect me ?!.de

Please send your application with your complete documents (cover letter, curriculum vitae, qualification certificates, references) to the following address, quoting the reference number A264-25 until 14.01.2026 as a PDF file by unencrypted electronic mail to:  bueroprotect me ?!.hungerprotect me ?!uni-bremen

Or by mail to 

Universität Bremen
SFB 1342 
Prof. Dr. Sophia Hunger
Postfach 33 04 40
28334 Bremen

We kindly ask you to send us only copies (no portfolios) of your application documents, as we cannot return them. They will be destroyed after the selection process has been completed. Any application costs cannot be reimbursed.

Please note that no photos are to be attached to the application documents.