Vilnius University

What you'll study

The programme delivers a balanced curriculum of life sciences and quantitative subjects. Core topics typically include molecular biology, genetics, cell biology, and laboratory techniques alongside mathematics, statistics and computer science.

• Programming and data analysis: practical training in languages and tools commonly used in bioinformatics such as Python, R, UNIX/Linux environments and version control.
• Mathematics and statistics: calculus, linear algebra, probability and statistical methods for analysing biological data and designing experiments.
• Computational biology: algorithms for sequence analysis, genome assembly, comparative genomics, machine learning applications and biological databases.
• Genomics and molecular techniques: introduction to next‑generation sequencing, transcriptomics, proteomics and hands‑on laboratory modules to provide context for computational work.
• Structural and systems bioinformatics: protein structure prediction, molecular modelling, network analysis and systems biology concepts.
• Practical project and dissertation: an independent research or applied project in the final year that develops problem‑solving, data handling and scientific communication skills.

The programme is delivered through lectures, practical computer and laboratory classes, seminars, group projects and an independent bachelor thesis. Elective modules allow students to deepen study in areas such as machine learning, medical informatics or synthetic biology. Mobility and internship opportunities with research institutes and industry partners are typically supported.

Entry requirements

Admission normally requires a completed secondary education certificate or equivalent. Strong preparation in mathematics is expected, and prior knowledge of biology or chemistry is advantageous. Applicants should demonstrate aptitude for quantitative reasoning and problem solving.

• Academic background: secondary school diploma with good results in mathematics; biology or chemistry is recommended.
• Language: proficiency in the language of instruction is required; applicants whose prior education was in a different language will typically need to provide recognised proof of language ability.
• Additional assessments: selection may include an entrance examination, written test, or interview to assess analytical and motivation aspects, and some programmes consider academic references or a personal statement.

International applicants should check the university's admissions pages for recognised qualification equivalency and accepted proofs of language proficiency.

Career prospects

Graduates are equipped to work at the interface of biology and data science. Typical career paths include:

• Bioinformatics analyst or software developer in biotechnology and pharmaceutical companies
• Data scientist or computational biologist in hospitals, clinical laboratories and public health organisations
• Research technician or junior researcher in academic institutes and government research centres focused on genomics, proteomics and systems biology
• Roles in health informatics, personalised medicine, and agricultural genomics
• Further academic study: graduates frequently continue to specialised MSc programmes (bioinformatics, computational biology, data science) or pursue PhD research

The combination of programming, statistical and laboratory knowledge makes graduates attractive to employers in both the life sciences and technology sectors, with opportunities in product development, data analysis, consulting and translational research.

Why study at Vilnius University

Vilnius University is one of the oldest and most comprehensive research universities in the region, offering interdisciplinary training that bridges life sciences and information technology. Students benefit from:

• Research links: collaboration with local research institutions and centres active in molecular biology, genomics and biotechnology provides project and internship opportunities.
• Cross‑faculty resources: access to laboratory facilities, computing infrastructure and expertise across faculties such as Biology, Chemistry and Mathematics and Informatics.
• Practical orientation: an emphasis on hands‑on practical classes, teamwork and applied projects that build employable technical skills.
• International connections: opportunities for student exchange and joint projects through European programmes and institutional partnerships.
• Location: Vilnius is an active hub for life sciences and IT startups, offering networking and internship options in a compact capital city environment.

Overall, the programme is suited to students seeking a rigorous, interdisciplinary grounding in the computational methods needed to work with modern biological data and to progress into research or industry roles.