Computer Science - Biocomputation Track
The Bachelor of Science in Computer Science – Biocomputation Track at University of Stanford integrates computer science, mathematics, and biology to explore complex biological systems using computational methods. In the early years, students build a strong foundation in programming, algorithms, data structures, calculus, linear algebra, and introductory biology. These courses develop analytical thinking, computational proficiency, problem-solving skills, and quantitative reasoning, enabling students to model and analyze biological processes effectively. Through lectures, laboratory exercises, and coding projects, learners gain essential tools to bridge biology and computation, preparing them for more advanced interdisciplinary studies.
As students progress, the program emphasizes bioinformatics, computational genomics, systems biology, machine learning applications in biology, and statistical modeling. Independent research projects, advanced seminars, and lab rotations refine students’ research methodology, technical expertise, data analysis skills, and critical evaluation. The honors curriculum encourages students to tackle real-world biological challenges through computational approaches, equipping them with both theoretical insight and practical experience. By graduation, students are prepared for careers in computational biology, bioinformatics, biotechnology, healthcare analytics, or further graduate study in computer science, biology, or interdisciplinary research.
Key information
Key Facts
- Program Title: Computer Science - Biocomputation 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 Biocomputation
• Introduction to Programming and Problem Solving
• Calculus and Linear Algebra
• General Biology I & II
• Data Structures and Algorithms
• Writing and Research in Computational Biology
Year 2 – Core Biocomputation Studies
• Molecular Biology and Genetics
• Statistics for Biological Data
• Software Development and Systems Programming
• Algorithms in Bioinformatics
• Seminar: Computational Biology Methods
Year 3 – Advanced Biocomputation Applications
• Genomics and Proteomics
• Systems Biology and Network Modeling
• Machine Learning for Biological Data
• Independent Research Projects
• Electives in Computational or Biological Sciences
Year 4 – Capstone and Honors Project
• Senior Thesis or Independent Research Project
• Advanced Seminar in Biocomputation
• Applied Computational Modeling
• Data Analysis and Biological Simulation
• Specialized Electives in Bioinformatics and Systems Biology
Career Opportunities
Graduates of this program are prepared for careers in computational biology, bioinformatics, biotechnology, healthcare analytics, research, and academia. The curriculum develops computational skills, biological understanding, analytical reasoning, and research proficiency, enabling students to pursue roles as bioinformaticians, computational biologists, research scientists, data analysts, or software developers in life sciences. Independent research and advanced projects provide practical experience, while the honors track strengthens preparation for graduate study or specialized professional roles. Graduates leave ready to apply computational methods to complex biological problems and contribute to innovation in science and healthcare.
Why Choose This Program
This program is ideal for students who wish to combine computer science and biology to address complex biological questions using computational techniques. Its structure emphasizes critical thinking, technical proficiency, research competence, and data analysis skills, providing students with both theoretical insight and practical experience. Through seminars, independent projects, laboratory work, and interdisciplinary research, learners develop the expertise to model biological systems, analyze large datasets, and solve real-world challenges in biotechnology and healthcare. Graduates leave with the knowledge, confidence, and professional readiness to pursue careers in computational biology, bioinformatics, research, or advanced academic study, contributing meaningfully to scientific innovation.
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
