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Computational Biology
The Bachelor of Arts in Computational Biology at Brown University offers students an interdisciplinary education combining biology, computer science, mathematics, and statistics to understand complex biological systems. The program emphasizes the use of computational modeling, data analysis, and algorithmic approaches to explore molecular biology, genetics, genomics, and systems biology. Students develop strong analytical and quantitative skills, learning to integrate computational tools with biological inquiry to address contemporary questions in medicine, biotechnology, and environmental science.
Throughout the program, students engage in laboratory research, computational projects, and collaborative problem-solving exercises. Coursework spans areas such as bioinformatics, systems biology, molecular modeling, and data-driven analysis of biological processes. Students are encouraged to participate in research initiatives, internships, and independent projects, gaining practical experience in applying computational techniques to real-world biological challenges. Graduates leave the program with critical thinking, quantitative analysis, and interdisciplinary research skills, prepared to contribute to scientific discovery, technological innovation, and advanced study in computational and life sciences.
Key information
Key Facts
- Program Title: Computational Biology
- Degree Type: Bachelor of Arts
- Duration: 4 years
- Mode of Study: Full-time, On Campus
- Application Deadline: 05 January 2026
- Location: Brown University, United States
- Field of Study: Biology
- Language of Instruction: English
Program Structure
Year 1 – Foundations in Biology and Computing
• General Biology I & II
• Introduction to Programming and Computational Methods
• Calculus and Linear Algebra
• Academic Writing and Scientific Research
Year 2 – Core Principles and Quantitative Methods
• Molecular and Cellular Biology
• Genetics and Genomics
• Statistics and Data Analysis for Biology
• Algorithm Design and Computational Techniques
Year 3 – Advanced Computational Biology
• Bioinformatics and Genomic Analysis
• Systems Biology
• Laboratory and Computational Research Methods
• Elective: Molecular Modeling, Neurobiology, or Evolutionary Biology
Year 4 – Capstone and Independent Research
• Senior Thesis or Research Project
• Advanced Seminar in Computational Biology
• Applied Data Science in Biological Contexts
• Electives: Biomedical Applications, Synthetic Biology, or Population Genetics
Career Opportunities
Graduates of the Computational Biology program are equipped with analytical, computational, and research skills, making them highly competitive in careers such as bioinformatics, computational research, biotechnology, pharmaceuticals, healthcare analytics, and environmental research. Alumni also pursue opportunities in academia, public health, medical research, and technology development, applying computational methods to advance understanding of biological systems. The program provides a strong foundation for graduate study in computational biology, bioinformatics, systems biology, medicine, or data science, enabling students to specialize further and contribute to cutting-edge research. Employers value graduates’ ability to analyze complex biological data, develop computational models, and provide data-driven solutions in scientific and technological contexts.
Why Choose This Program
This program offers a unique interdisciplinary education that combines biology, computer science, and quantitative analysis, preparing students to tackle contemporary challenges in life sciences. Students benefit from faculty mentorship, research opportunities, and hands-on computational and laboratory experience, fostering both theoretical understanding and practical expertise. The curriculum emphasizes critical thinking, data interpretation, and problem-solving, enabling graduates to address complex biological questions and innovate in research, technology, and healthcare. By integrating computational methods with biological insight, the program equips students with the skills, knowledge, and perspective needed to excel in scientific research, industry, and graduate study, while contributing to the advancement of computational and life sciences.
Contact Information
For further information, please contact the admissions office at:
Phone: +1 401 863 1000
Email: admissions@brown.edu
Address: University of Brown, Providence, RI 02912, United States
