Life Sciences – Specialization in Computational Biology (.M.Sc)

עברית

What will you study, and why should you study at Bar-Ilan?

.M.Sc

Today’s biology goes far beyond traditional laboratory experiments. Advances in technology—from high-throughput genome sequencing and advanced imaging to real-time tracking of gene and cellular activity—have turned every biological experiment into a massive source of data. To truly understand what happens in the body during disease or how treatments develop and take effect, scientists must speak the language of data.

This is where computational biology comes in: a fusion of biology, mathematics, and programming that translates data into insights driving breakthroughs in science and medicine. If you want to be among those making scientific decisions, interpreting results rather than simply measuring them, this is the language of modern research.

The M.Sc. with a specialization in Computational Biology at Bar-Ilan University places you at the forefront of this field. Here, you learn to turn data into a driving force for research: building mathematical models of biological systems, analyzing genetic sequences, interpreting omics data, and developing algorithms that explain how life functions at the gene, cell, and organism levels. These skills are already powering personalized medicine, drug development, advanced genomics, and next-generation biotechnologies—and opening doors to highly sought-after careers in bioinformatics, research, and innovation.

 

The demand for graduates in Computational Biology is steadily increasing. Organizations in the scientific and technological industries are seeking professionals capable of extracting insights from complex biological data.

Graduates of the program pursue roles such as:

  • Biological data analysts in research and genetics institutes

  • Researchers in biotechnology, pharmaceutical, and neuroscience companies

  • Algorithm and machine learning developers for biological applications

  • R&D positions in companies specializing in sequencing, genomics, and medical information systems

  • Research and development in data-driven biological start-ups

  • Research assistants and computational lab managers in academic institutions

  • Positions in clinical laboratories and companies involved in clinical trials and genetic regulation

The program is completed over two years and comprises a total of 40 credits:

  • 24 credits of advanced courses and seminars

  • 16 credits for a supervised research thesis

  • Annual participation in the departmental colloquium

The first phase of the program focuses on building a strong scientific foundation and familiarizing students with the research environment. In the second phase, students conduct an independent research project, including experimental design, data collection, and thesis writing.

Advanced Courses and Seminars

Students choose from a variety of courses in bioinformatics, machine learning, systems biology modeling, and omics data analysis.
Participation in two seminars is required (one computational and one either computational or biology-focused).
Up to 4 credits may be taken from relevant courses in other departments.

Elective Courses

The remaining credits can be completed through elective courses in areas such as:

  • Computational genomics

  • Machine learning and data analysis

  • High-throughput data processing

  • Systems biology modeling

  • Structural biology and other computational applications

Up to 4 credits may be taken from relevant courses in other departments.

Seminars and Research Proposal

  • Two seminars are held during the program

  • Submission of a research proposal at the end of the first year

  • Annual enrollment in the departmental colloquium (no credits)

Computational biology combines deep biological understanding with advanced computational skills. In the M.Sc. program, you will engage directly with computational-biology research, working with real datasets that reflect the challenges of modern science.

During the program, you will:

  • Analyze real datasets from genetics, epigenetics, systems biology, and neuroscience

  • Develop computational models to understand biological processes, genetic regulation, and molecular interactions

  • Apply advanced methods in machine learning, omics analysis, and high-throughput data processing

  • Work with bioinformatics tools, algorithms, and analytical platforms to uncover complex biological patterns

  • Receive personalized guidance from leading researchers while developing skills in independent work, precise analytical thinking, and professional academic presentation

Hands-on experience will allow you to build genuine expertise at the interface of biology and data—a skill set highly valued in biotechnology, digital medicine, genomics, and other scientific and technological fields.

  • A relevant bachelor’s degree in Computational Biology with an average grade of 80 or above

  • Applicants with an average below 85 may be required to attend an admissions interview

  • Graduates of Life Sciences or Computer Science may need to complete prerequisite courses

  • In some cases, applicants from other backgrounds may be considered, subject to the approval of the admissions committee and the supervisor

  • Securing a supervisor in the computational field and obtaining their approval is mandatory

  • Lists of potential supervisors are available on the Faculty website

Want to learn more about the M.Sc. in Life Sciences with a specialization in Computational Biology?

 

Last Updated Date : 18/01/2026