Master of Science in Bioinformatics

Overview

Life-science and medical research increasingly depend on interpreting large-scale biological data, making computational methods, mathematical models, and efficient algorithms essential tools. This English-taught, interdisciplinary Master’s builds on the foundations acquired in a bachelor’s degree in bioinformatics and advances students’ skills across mathematics, computer science, biology, and translational bioinformatics. The curriculum blends rigorous theoretical courses with applied training so students learn to formulate relevant biological questions, design appropriate mathematical or computational approaches, and interpret results in biological or biomedical contexts.

The programme is offered jointly by the Department of Mathematics and Computer Science, the Department of Biology, Chemistry and Pharmacy, and the Charité Medical School, reflecting a strong link between basic life-science research and clinical translation. Training emphasizes practical data analysis and modelling techniques that are directly relevant to contemporary challenges in genomics, systems biology, and biomedical data science.

Specialisations

• Complex Systems — advanced modelling, simulation, and analysis methods for networks and dynamic processes, from molecular interaction networks to ecological systems.
• Data Science — state-of-the-art statistical and machine-learning techniques for extracting knowledge from realistic and large-scale data sets, with attention to data-generation effects and big-data issues.
• Advanced Algorithms — design and analysis of efficient algorithms for bioinformatics tasks, including indexing very large sequencing data and methods for protein and RNA analysis.

What this prepares you for

Graduates are prepared for research and development roles in academia, clinical research settings, biotech and pharmaceutical industries, and healthcare informatics, as well as for doctoral studies. The programme’s mix of theory and hands-on application, together with the Charité connection, is particularly relevant for students interested in translational bioinformatics or medically oriented data science.

Requirements and prerequisites

• A completed bachelor’s degree in bioinformatics (or an equivalent degree with comparable subject knowledge)
• Solid background in mathematics, computer science and biology as covered in a bioinformatics bachelor’s programme
• Programme language: English; instruction and coursework are provided in English

Overview of the curriculum

The programme begins with a concentrated first-semester "basic studies" phase (30 CP) made up of three core modules (6 CP each). Each core module includes a lecture plus an exercise/tutorial and is designed to reinforce the methodological foundations you need across disciplines: computer science, mathematics & statistics, and bio-medicine. In parallel there is a 12 CP introductory module (lecture series + seminar) that presents the three available profile areas—Advanced Algorithms, Complex Systems and Data Science—to help you choose the specialization that best matches your interests and career goals.

From the second semester you specialise by selecting one of the three profile areas (profile area = 30 CP). Each profile area combines a 15 CP Focus Area, a 10 CP research internship (hands‑on research experience), and a 5 CP module on Ethics and Policy Questions. The mandatory focus modules differ by profile:

• Complex Systems: Complex Systems in Bioinformatics (10 CP) and Complex Systems in Biomedical Applications (5 CP)
• Data Science: Data Science in the Life Sciences (15 CP)
• Advanced Algorithms: Advanced Algorithms for Bioinformatics (10 CP) and Methods in Life Sciences (5 CP)

The programme also includes a 30 CP elective area where you may choose profile modules and other optional modules from the programme’s elective list, subject to a few constraints that ensure breadth and practical experience. The master’s thesis (30 CP) is typically completed in the fourth semester; you have 23 weeks to work on it and are expected to give a 30‑minute presentation on your progress during the writing period.

Key learning outcomes (what you will gain)

• Solid interdisciplinary foundations in computing, quantitative methods and biomedical knowledge to tackle bioinformatics problems.
• Applied skills in your chosen profile—modeling and systems thinking for Complex Systems; large‑scale data analysis and machine learning for Data Science; algorithm design and computational methods for Advanced Algorithms.
• Practical research experience through the research internship and the master’s thesis, plus an awareness of ethical and policy implications of life‑science computing.
• Experience in both theoretical (lecture/tutorial) and practical (research/practical modules) formats preparing you for research or industry roles.

Concise programme requirements (credit point = CP)

• Basic studies: three core modules, 6 CP each, to be completed in the first semester (each module = lecture + exercise/tutorial). Modules: Foundations in Computer Science; Foundations in Mathematics and Statistics; Foundations in Bio‑Medicine.
• Introductory module: 12 CP (lecture series + seminar) introducing the three profile areas.
• Profile area (30 CP, starts in semester 2): includes one Focus Area (15 CP), Research Internship (10 CP), Ethics and Policy Questions (5 CP).
  • Complex Systems focus: Complex Systems in Bioinformatics (10 CP) and Complex Systems in Biomedical Applications (5 CP).
  • Data Science focus: Data Science in the Life Sciences (15 CP).
  • Advanced Algorithms focus: Advanced Algorithms for Bioinformatics (10 CP) and Methods in Life Sciences (5 CP).
• Elective area: 30 CP from the programme’s optional modules with the following constraints:
  • At least 10 CP of profile modules from your chosen profile area.
  • At least one V‑module (lecture-format) must be selected and completed.
  • At least one practical module must be selected and completed.
• Master’s thesis + colloquium: 30 CP; usual timing in the fourth semester, 23 weeks processing time, and a 30‑minute progress presentation during the thesis period.

Further information and detailed module lists are available in the programme’s Online Studies Selection Guide (OSA) and on the programme website (PDF downloads and full module descriptions).

Graduates are prepared for roles in academic research, biotech and pharmaceutical companies, medical informatics and health‑tech startups, public health and governmental agencies, and research institutions. Typical positions include bioinformatics scientist/analyst, computational biologist, data scientist for life‑science applications, algorithm developer for genomics, and roles in translational medicine.

The degree also provides a strong foundation for doctoral studies (PhD) in bioinformatics, computational biology or related fields. Being based in Berlin offers access to a dense network of research centres, hospitals and industry partners for further career development and collaborations.