Hannover Medical School
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PhD Programme in Biomedical Data Science (BIOMEDAS) at Hannover Medical School Hannover Medical School in Germany
Degree Level
PhD
Field of study
Computer Science
Funding
Available
Deadline
Oct 31, 2026
Country
Germany
University
Hannover Medical School

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About this position
The PhD programme in Biomedical Data Science (BIOMEDAS) at Hannover Medical School (MHH) offers an interdisciplinary research environment at the interface of life sciences, health sciences, and advanced data science. The programme is conducted in cooperation with several leading institutions, including Leibniz University Hannover, Helmholtz Institute for Infection Research Braunschweig, Technical University Braunschweig, University of Veterinary Medicine Hannover, Ostfalia University, Fraunhofer Institute, and other research partners in the Hannover region.
BIOMEDAS is designed for students who wish to combine disciplinary expertise in computer science or life sciences with skills in biomedical data science. The curriculum covers bioinformatics, medical informatics, databases, data mining, machine learning, applied mathematics, biomedical modelling, and analysis of complex networks. Students engage in joint data science projects across partner institutions, fostering interdisciplinary exchange and collaboration.
Research topics include exploiting biomedical and clinical data sources, advancing personalised medicine, understanding pathomechanisms through biomathematical modelling, and employing artificial intelligence for tailored diagnostics and treatment strategies. The programme applies a collaborative training principle, with annual meetings of the thesis advisory committee and a combination of core research projects and individual courses. International elements include guest lecturers, specialist literature, language training, and intercultural skills development. Integrated German and English language courses are available.
All PhD students are financially supported, typically through their supervisor. There are no tuition fees, but a semester contribution of about 400 EUR applies. Living costs are estimated at 1,000 EUR per month. Accommodation in student hostels is possible. The programme duration is six semesters, beginning in the winter semester. Applicants must hold a university degree in computer science-related fields (medical computer science, bioinformatics, physics, engineering, computer science, statistics, mathematics) or health science-related fields (medicine, veterinary medicine, pharmacy, life sciences). Computer science applicants must demonstrate understanding of biomedical research; health science applicants must show competence in data science. Excellent English language skills are required.
Application is via the DAAD portal. The programme offers structured research and supervision, research training, career advisory services, and support for international students, including welcome events, tutors, cultural and linguistic preparation, visa assistance, and pick-up service. For more information, visit the programme website or contact the programme via email.
Funding details
Available
What's required
Applicants must have a successfully completed university degree in computer science related fields (such as medical computer science, bioinformatics, physics, engineering, computer science, statistics, mathematics) or in health science related fields (such as medicine, veterinary medicine, pharmacy, life sciences). Computer science applicants must demonstrate adequate understanding of biomedical research; health science applicants must demonstrate competence in data science. Proof must be submitted to the programme commission, which may propose further qualification measures in consultation with the supervisor. Excellent English language skills are required.
How to apply
Submit your application via the DAAD portal at the provided link. Ensure you meet the academic and language requirements. Prepare documentation to demonstrate your background in biomedical data science. For questions, contact the programme via the provided email address.
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