Carnegie Mellon University’s Bachelor of Science in Computational Biology (BSCB) is a leading interdisciplinary degree housed within the School of Computer Science (SCS). Designed for students with a passion for both computer science and the life sciences, this rigorous program integrates coursework in biology, computer science, mathematics, and statistics to equip students with the skills needed to analyze and model complex biological systems.
The program emphasizes a strong research foundation, encouraging all students to participate in hands-on undergraduate research—a unique guarantee by the department. With broad applicability in biotechnology, pharmaceuticals, biomedical research, and data science, the BSCB prepares students for both industry careers and advanced studies in graduate or medical school.
University Ranking Highlights:
Top 5 globally for Computer Science (U.S. News & World Report, 2024)
CMU is internationally recognized for contributions in computational biology, machine learning, and systems biology
Faculty include leading researchers in bioinformatics, genomics, and AI-driven biology
Course Overview
Mathematics & Statistics Core: Differential and Integral Calculus and Integration, Differential Equations, and Approximation, Mathematical Foundations for Computer Science, Probability Theory for Computer Scientists, Introduction to Statistical Inference, Mathematical Statistics (Honors), Probability and Statistical Inference I, Probability and Computing, Matrices and Linear Transformations, Matrix Theory
General Science Core: Introduction to Modern Chemistry I, Honors Chemistry: Fundamentals, Concepts and Applications, Physics I for Science Students, Physics I for Engineering Students
Biological Core: Honors Modern Biology, Modern Biology, Genomes, Evolution, and Disease: Introduction to Quantitative Genetic Analysis, Biochemistry I, Honors Biochemistry, Cell Biology
Computer Science Core: First-year Immigration Course, Principles of Imperative Computation, Great Ideas in Theoretical Computer Science, Algorithm Design and Analysis, Algorithms and Advanced Data Structures, Introduction to Machine Learning (SCS Majors), Introduction to Machine Learning
Computational Biology Core: Programming for Scientists, Fundamentals of Programming and Computer Science, Great Ideas in Computational Biology I and Great Ideas, in Computational Biology II, Quantitative Cell and Molecular Biology Laboratory, Computation and Biology Integrated Research Lab, Computational Biology Seminar, Computational Genomics, Computational Methods for Biological Modeling and Simulation
General Education: Interpretation and Argument, Advanced First Year Writing: Special Topics, Cognition, Choice, and Behavior Elective, Economics, Political, and Social Institutions Elective, Cultural Analysis Elective, Non-technical Electives (x3)
Sample Course Plan (Flexible):
Years 1 & 2: Core biology, math, CS, and foundational computational biology
Years 3 & 4: Advanced modeling, machine learning, research participation, electives
Research guaranteed: Access to world-class CMU labs
Project-based coursework in modeling, genomics, and simulation
Interdisciplinary collaboration across SCS, biology, and engineering departments
Opportunities for internships in biotech, pharma, and health data analytics
Pathway to additional major or minor in Computational Biology for students in other CMU departments
Graduates accepted into top graduate and medical schools globally
High demand across industries: biotech, pharmaceuticals, AI in medicine, academia
Research and algorithmic training make graduates competitive for PhDs, MD/PhD programs, and technical roles in life sciences
Strong pathway to Carnegie Mellon’s MS or PhD programs in Computational Biology or Machine Learning
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