Course prerequisites

To be admitted to the Computational Biology PhD program, you must have completed coursework in the following areas:

• Mathematics through Linear Algebra
• At least one course in Statistics
• At least one course in Computer Science
• At least one course in Molecular Biology

Competitive students lacking one or more of these requirements will be expected to satisfy these prerequisites prior to or during their first year, or to secure approval from the Director of Graduate Studies based on similar coursework or experience. So if you want to make your application more competitive, ensure your coursework satisfies these prerequisites at a minimum.

Essential skills

Beyond the formal prerequisites, successful applicants typically demonstrate proficiency in several key areas. Consider developing skills in:

• Programming languages - Python and R are the most common languages used in computational biology
• Data analysis - Experience with statistical analysis, data visualization, and machine learning
• Software ecosystems - Experience with computational infrastructure best practices, like command line, git, collaborative coding practices
• Biological data - Understanding of genomics, transcriptomics, or other biological data

What we look for in applicants

1. Tangible research output

The purpose of a PhD is to create new knowledge. The best predictor of future performance is past performance. We look for evidence that you can produce tangible research outputs, such as:

• Research papers or preprints, in journals we recognize
• Conference presentations or posters
• Open-source software contributions
• Undergraduate thesis or research projects
• Summer research experiences at academic or industry labs

2. Computational experience

Computational biology research requires strong computational skills. We look for students with depth in computational training, demonstrated through:

• Programming projects or coursework
• Experience with data analysis pipelines
• Algorithm development or implementation
• Computational research experience

3. Understanding of biology

A deep understanding of biology is essential. The specific area matters less than having a strong foundation on which to build specialized knowledge. Evidence includes:

• Upper-level biology coursework
• Laboratory research experience
• Understanding of molecular and cellular processes
• Ability to connect computational approaches to biological questions

4. Clear communication

Science requires clear communication. We look for applicants who can:

• Clearly articulate the broad scientific hypothesis or question of their research
• Explain complex concepts in accessible language
• Write concise and well-organized research statements
• Present their work effectively to diverse audiences

Strengthening your application

To prepare a competitive application, consider:

• Gain research experience - Seek opportunities in computational biology labs, either at your institution or through summer programs
• Take relevant coursework - Beyond prerequisites, consider courses in machine learning, bioinformatics, genomics, or systems biology
• Build your skills - Work on independent projects, contribute to open-source software, or analyze publicly available biological datasets