# The Computational Biology Major

**Source**: https://www.cmu.edu/cbd/education/undergraduate/bs-computational-biology/index.html
**Parent**: https://www.cs.cmu.edu/academics/undergraduate/programs

# About the Bachelor of Science in Computational Biology

All undergraduates accepted to the School of Computer Science at Carnegie Mellon University are able to choose between four majors: computational biology, computer science, artificial intelligence, and human-computer interaction. For more information on the different majors, please visit the [School of Computer Science Undergraduate Programs Overview](https://www.cs.cmu.edu/undergraduate-programs).

Success in computational biology requires significant technical knowledge of fundamental computer science as well as a broad biological intuition and general understanding of experimental biology. However, most importantly, it requires students who can integrate their knowledge by making connections between the two fields.

As much as any other field, making the interdisciplinary connections required to truly integrate biological and computational knowledge often requires a student to conduct research. We don't just encourage undergraduate research to our majors; we *promise* it to all students who are interested.

There is significant industry demand for excellent computational biology students, in biotech firms, biomedical research, as well as in pharmaceutical research.  Both established companies and the hundreds of recent startups in this field struggle to find computationally sophisticated employees who have a strong foundation in the life sciences. By receiving their training in the world-famous School of Computer Science, our students will receive a degree that is unparalleled at any other institution.

Students completing the major will also be ideally prepared for Ph.D. programs across a range of biomedical areas. Students who choose to complete pre-med requirements will be very well-prepared to attend medical school; the next generation of physicians will need to better understand the computational approaches needed for automated medical testing, automated medical imaging, and the revolution in personalized medicine.