This master's programme brings together biological sciences and computational approaches to study living systems. It focuses on bioinformatics and systems biology, teaching you how to analyse and model molecular and biochemical data. Much of the curriculum centres on the interpretation of high-throughput “omics” datasets — genomics, transcriptomics, proteomics and metabolomics — to understand biological processes at systems level.
You will gain both conceptual and practical skills for handling large biological datasets: statistical analysis, computational modelling and algorithmic approaches used in molecular biology. Computational training is complemented by hands-on wet-lab experience, so you learn to connect experimental design and data generation with downstream data analysis. Graduates leave with a solid biological foundation and the ability to understand, adapt or develop software tools for processing and interpreting biological data.
The programme equips you for interdisciplinary careers in academic research, biotech and pharmaceutical industries, or for further doctoral study. Its combination of lab-based training and computational proficiency is particularly valuable for roles that require bridging molecular experiments and data-driven analysis.
The complete curriculum and detailed programme structure are available as a downloadable PDF on the course website. That document is the authoritative source for module listings, credit allocation, semester-by-semester planning and the official learning outcomes associated with each course component.
In the programme document you can expect to find which courses are designated as core versus elective, how the Master's research project or thesis is integrated, and how assessments are organised across the study period. The learning outcomes section explains the knowledge, technical skills and competencies you are expected to achieve by graduation, and the module descriptions clarify the scope and content of each course.
For international applicants it is especially helpful to consult the PDF before applying: it will let you plan your prior-study equivalence, check required language qualifications, estimate workload and credits per semester, and identify contact persons for academic or administrative questions.
Key items to check in the downloadable programme structure:
You must hold a Bachelor's degree of at least six semesters totaling 180 ECTS (European Credit Transfer and Accumulation System). Up to 30 ECTS may be submitted after admission, so meeting the full 180 ECTS requirement can be completed partially post-admission.
In addition to the overall degree credit requirement, your prior coursework must show a strong foundation in biology/bioinformatics and quantitative subjects. There are two alternative subject combinations that are accepted — each specifies minimum ECTS in biological/bioinformatics topics and in mathematics/quantitative disciplines.
Minimum overall qualification:
Subject-area requirements (one of the following combinations):
If your degree or course distribution differs from these exact combinations, contact the programme’s admissions office for an individual evaluation of your transcripts.
Winter Semester (International)
15 February 2027
Winter Semester (EU/EEA)
15 May 2026
Graduates are prepared for research and development roles in academia, research institutes and the life sciences industry (biotechnology, pharmaceuticals) where skills in omics data analysis and computational modelling are in demand. They can work as bioinformaticians, computational biologists, data scientists for biological datasets, or in roles developing software tools for molecular data analysis.
The programme also provides a solid foundation for doctoral studies in computational biology, systems biology or related fields, enabling students to pursue a research career or specialized positions that bridge biology and computational sciences.