Bioinformatics sits at the intersection of biology, computer science and mathematics and is driving many of the advances that will shape medicine, agriculture and biotechnology. At its heart are computational methods for analysing large-scale biological data so we can uncover the organizing principles and functions of complex biological systems. These capabilities underpin modern systems biology, systems medicine and systems genetics, enabling developments such as more personalised and effective medical treatments, discovery of new drugs, and improved food quality and safety.
This English-language Master of Science programme at the University of Potsdam (Bergholz-Rehbrücke campus) equips students with the methodological and analytical skills needed to handle diverse biological data produced by modern technologies. The curriculum is designed to train students to tackle cross-disciplinary problems in bioinformatics, with a strong emphasis on developing and applying computational techniques for real-world biological and biomedical questions.
The programme is aimed at applicants who already have a solid foundation in quantitative or life sciences and who want to deepen their ability to analyse biological systems computationally. Because bioinformatics integrates concepts from multiple fields, prior knowledge in natural sciences or computer science is a clear advantage for success in the course. Graduates leave prepared to contribute to research and development efforts where large-scale data analysis and systems-level understanding are essential.
Requirements (summary)
The programme’s complete curriculum — including the semester-by-semester structure and how courses are organised — is provided in the downloadable PDF linked on the programme webpage. That official document is the authoritative source for module descriptions, credit weighting, assessment formats and the formal rules governing progression and the master’s thesis.
Within the PDF you will find the full list of core and elective modules together with their learning objectives and expected outcomes. These module entries typically specify the competencies you will gain (knowledge, practical skills, and transferable abilities), the workload in ECTS credits, prerequisites (if any), and the assessment methods used to measure achievement.
For international applicants it’s useful to check the PDF for a few specific items: the breakdown of compulsory versus elective courses, any laboratory or project components, the thesis requirements and expected duration, and language of instruction. If anything in the document is unclear, contact the programme coordinator or admissions office named on the programme page for clarification.
Requirements — where to find them and what to check
Please consult the program’s official admission webpage for the authoritative, up-to-date list of all entry requirements and application procedures. The program website contains the full details you must follow — including eligibility criteria, required documents, application deadlines, fees (if any), and contact information for the admissions office.
As an international applicant, make sure you allow time for document translation, certification of copies, and any visa or funding documentation. The program page will also tell you whether proof of language skills, degree recognition, or additional assessments are needed — check it carefully and contact the admissions team if anything is unclear.
Winter Semester (International)
The deadline depends on a NC restriction (numerus clausus – a restriction on admission because there are more applicants than available places). All information concerning the application deadlines can be foundhere.
Graduates are prepared for roles that require advanced computational and analytical skills applied to biological data, including positions in biotech and pharmaceutical companies (bioinformatics analyst, computational biologist, data scientist), research institutes, and health technology firms. The programme’s emphasis on systems biology, systems medicine and systems genetics aligns graduates with work in personalised medicine, drug discovery and translational research aimed at improving diagnostics and therapies. Many graduates also pursue academic research or PhD programmes in computational biology, genomics or related fields, or work in interdisciplinary teams developing algorithms, pipelines and software for large-scale data analysis in industry, clinical environments and public research institutions.
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