Mathematical and Computational Science - Biology Track
The Bachelor of Science in Mathematical and Computational Science – Biology Track at University of Stanford provides an interdisciplinary approach to understanding biological systems through quantitative and computational methods. In the first year, students develop a strong foundation in mathematics, biology, chemistry, and computer programming. These courses foster analytical thinking, problem-solving skills, quantitative reasoning, and research proficiency, allowing students to apply mathematical models and computational techniques to biological problems. Through lectures, laboratory exercises, and hands-on projects, learners gain practical experience in data analysis, statistical modeling, and computational simulations relevant to modern biology.
As students advance, the curriculum emphasizes computational biology, bioinformatics, systems biology, mathematical modeling of biological processes, and advanced laboratory research. Independent research projects, seminars, and interdisciplinary coursework refine students’ technical expertise, research methodology, critical evaluation, and applied problem-solving skills. The honors curriculum encourages students to design innovative computational models, conduct biological simulations, and integrate mathematical techniques with experimental biology. By graduation, students are prepared for careers in biotechnology, bioinformatics, computational biology, medical research, or advanced graduate study in biological or computational sciences.
Key information
Key Facts
- Program Title: Mathematical and Computational Science - Biology Track
- Degree Type: Bachelor of Science
- Duration: 4 years
- Mode of Study: Full-time, On Campus
- Application Deadline: 05 January 2026
- Location: Stanford University, United States
- Field of Study: Biology
- Language of Instruction: English
Program Structure
Year 1 – Foundations in Mathematical and Computational Biology
• Calculus and Linear Algebra
• Introduction to Biology and Chemistry
• Programming and Computational Methods
• Writing and Research in Biological Sciences
• Introduction to Quantitative Modeling
Year 2 – Core Computational Biology Studies
• Molecular and Cellular Biology
• Statistics and Data Analysis
• Systems Biology
• Bioinformatics
• Seminar: Research Methods in Computational Biology
Year 3 – Advanced Applications
• Mathematical Modeling of Biological Processes
• Genomics and Proteomics
• Computational Simulation Projects
• Independent Research Projects
• Electives in Advanced Biology or Computational Methods
Year 4 – Capstone and Honors Project
• Senior Thesis or Independent Research Project
• Advanced Seminar in Mathematical and Computational Biology
• Applied Data Analysis and Computational Modeling
• Interdisciplinary Laboratory Projects
• Specialized Electives in Computational Biology
Career Opportunities
Graduates of this program are equipped for careers in biotechnology, bioinformatics, computational biology, medical research, data analysis, and computational modeling in biological systems. The curriculum develops technical proficiency, analytical skills, problem-solving ability, and research expertise, enabling students to pursue roles as computational biologists, bioinformaticians, laboratory researchers, data analysts, or biotechnology specialists. Hands-on experience through independent research projects, laboratory work, and computational modeling ensures that graduates are prepared to tackle complex biological questions using quantitative and computational approaches. Furthermore, the program lays a strong foundation for advanced graduate study, including PhD or professional degrees, allowing students to expand their expertise in computational life sciences and interdisciplinary research.
Why Choose This Program
This program is ideal for students who wish to combine mathematics, computation, and biology to address complex questions in the life sciences. Its structure emphasizes critical thinking, quantitative reasoning, research methodology, and applied problem-solving, providing students with both theoretical knowledge and practical experience. Through seminars, independent research, computational modeling projects, and interdisciplinary laboratory work, learners develop the skills to analyze biological systems, design predictive models, and interpret complex datasets. Graduates leave with the expertise, confidence, and professional readiness to pursue careers in biotechnology, computational biology, medical research, data science, or advanced academic study, while also gaining the flexibility to adapt to rapidly evolving scientific and technological landscapes.
Contact Information
For further information, please contact the admissions office at:
Phone: +1 650 000 0000
Email: admissions@standord.edu
Address: University of Standord, 450 Serra Mall, Stanford, CA 94305, United States
