Overview This intensive, two-semester Master’s programme (AMSR) provides advanced, research-focused training in social science methods. It strengthens your ability to plan and carry out independent research by deepening skills in research design, data collection, and both qualitative and quantitative analysis. The course is taught in English and aimed at an international student body.
What you will learn You will broaden your methodological toolkit with advanced research designs and specialised techniques such as data visualisation, a range of statistical methods, and qualitative discourse analysis. Course work is linked to applied research themes—Inequality and Diversity, Digital Societies, and International Politics and Conflict—so you can practise and refine methods on socially and politically relevant topics. The programme emphasizes both theory and practical application and concludes with a Master’s thesis. It is particularly suitable for students planning to continue on to a PhD.
Requirements and key facts
The curriculum is organised around three core components: Research Methods, Research Fields and the Master's Thesis. Together these strands ensure you build a solid methodological foundation, apply those methods to substantive social-science questions, and demonstrate your ability to carry out an independent research project.
Research Methods concentrates on the practical and theoretical tools used in contemporary social-science research. Expect to develop strong skills in research design, data collection and data analysis so you can select and apply appropriate methods to real-world problems. Learning outcomes include methodological competence, critical evaluation of empirical work, and the ability to handle and interpret data relevant to social-science inquiries.
Research Fields provide the substantive contexts in which you apply methodological skills. These modules train you to contextualise methods within specific social-science topics and to engage with current debates in one or more thematic areas. The Master’s Thesis is the programme’s capstone: a supervised, independent research project in which you formulate a clear question, design and implement an empirical strategy, analyse results and present your findings in written form.
Further details and a full list of modules can be found in the programme’s module catalogue: https://www.uni-marburg.de/en/fb03/studying/english-study-programs-m-a/ma-amsr/structure.PDF
Requirements (concise)
Admission requirements
You should hold a relevant Bachelor's degree in Social Sciences or an equivalent foreign degree. The final degree must meet a minimum academic standard of 2.7 on the German grading scale. Applicants whose degrees are evaluated as comparable by the admissions office are also eligible.
If your final degree certificate is not yet available by the application deadline, the program may allow provisional enrollment until the degree is completed. This makes the program accessible to applicants who are finishing their undergraduate studies at the time of application.
There is a specific methods prerequisite: you must have completed at least 10 ECTS credits in social science methods during your prior study program. Of those, a minimum of 5 ECTS must be in quantitative methods and/or statistics (these credits typically come from undergraduate courses in research methods, statistics, or related modules).
Key requirements (concise)
Winter Semester (International)
https://www.uni-marburg.de/en/studying/after-your-first-degree/masters-programs/application-for-a-masters-programme/master-application-deadlines
Graduates gain the methodological expertise needed for further academic qualifications (PhD) as well as for research-oriented roles in policy institutes, think tanks, NGOs, international organisations and applied research units. The programme’s strong emphasis on quantitative and qualitative methods also prepares students for positions as data analysts, research consultants, or policy researchers in public and private sectors.
The skills acquired—advanced research design, statistical analysis, data visualisation and qualitative methods—are highly transferable and valued in interdisciplinary teams that address socially and politically relevant problems.