PhD Programme in Biomedical Data Science

The PhD Programme in Biomedical Data Science at Hannover Medical School (MHH) trains doctoral candidates at the intersection of data science and life sciences. Students combine disciplinary expertise in bioinformatics, medical informatics, databases, data mining, machine learning, and related fields with biomedical research skills. Supervision is provided by researchers from MHH and multiple regional partner institutions. The programme awards a PhD or Dr. rer. nat. degree.

Academic requirements

Applicants from computer science must demonstrate adequate understanding of biomedical research; applicants from health sciences must demonstrate competence in data science. The programme commission may propose further qualification measures.

Minimum GPA

not_published

English requirements

Excellent command of English required. No specific standardised test score is listed on the DAAD page.

Accepted bachelor fields

Completed university degree in computer-science-related fields (e.g. medical computer science, bioinformatics, physics, engineering, computer science, statistics, mathematics) or health-science-related fields (e.g. medicine, veterinary medicine, pharmacy, life sciences). Computer science applicants must demonstrate biomedical research understanding; health science applicants must demonstrate data science competence.

APS Certificate

not_published

Tuition fee

None. Doctoral candidates at Hannover Medical School are funded researchers. Only the semester contribution (Semesterbeitrag) applies.

Semester contribution

Approx. 400 EUR per semester (DAAD source). Identical for EU and non-EU doctoral candidates.

ECTS credits

180

Funding info

Tuition: None. Doctoral candidates at Hannover Medical School are funded researchers. Only the semester contribution (Semesterbeitrag) applies. Semester contribution: Approx. 400 EUR per semester (DAAD source). Identical for EU and non-EU doctoral candidates.

Graduates are prepared for careers as data scientists and translational researchers in academic, clinical, and industry settings at the intersection of biomedical research and digital data science.

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