Molecular genetics is increasingly driven by data and technology. Computational biology is playing a critical role in these advances. Computational biologists use methods from physics, math or computer science to model biological processes or analyse genomic data, for example. The availability and continuing generation of large-scale datasets and data analysis has created a high demand for researchers with advanced computational skills who also have a strong grasp on molecular biology.
The CBMG track aims to provide students with an immersive computational biology education. Students are admitted to the Molecular Genetics PhD program and are provided opportunities and courses specific to their discipline to maximize their training potential.
Professor Tim Hughes, Rm 1302, Donnelly Centre, 160 College St., M5S 3E1
Professor Fritz Roth, Rm 1010 Donnelly Centre
Professor Quaid Morris, Rm 616, Donnelly Centre
- Guided reading: During the summer before the official start of graduate studies, we will give you essential reading material to complement your undergraduate education.
- Summer placement: You’ will get hands-on experience in computational molecular genetics as a paid intern.
- Rotations: In the fall of the 1st year, you'll take three five-week rotations before joining your thesis lab.
- Molecular Biology, Genomics, & Computational Biology: In the fall of the 1st year, we will teach you about diverse current research topics relevant to computational biology (Professor Tim Hughes).
- Graduate Computational Biology: In the winter of the 1st year, you will take an intensive hands-on course in computational biology (Professors Fritz Roth and Quaid Morris).
- Thesis topic: You may choose any topic within the many fields of study represented in the department. Most labs rely on genomic and computational technologies in some way, and for many it is their primary focus.
- Socializing: Annual retreats, and other social & scientific events to help you meet other Molecular Genetics students at all stages of their PhDs.
All successful CBMG applicants will be admitted directly into the Ph.D. Program. Admissions requires:
- A Bachelor’s degree in life sciences or quantitative disciplines (physics, math/stats, computer science, chemistry or engineering).
- An undergraduate average of A- or higher (or equivalent).
- Evidence of comfort and ease with computer programming, e.g. academic excellence in multiple computer courses, computational research, programming through employment or extracurricular activities.
- Academic excellence in two or more quantitative subjects: calculus, linear algebra,
probability/statistics or other math or quantitative courses.
- Research experience outside the classroom — wet or dry, biological or non-biological.This includes summer studentships, a lab job that involves working on scientific problems and most fourth-year honours projects.
- A completed online application form indicating "CBMG" in the "Proposed Area of Study".
- At least two letters of reference.
- A letter of intent - be sure to explain your interest in the CBMG Ph.D. track.
- A successful interview.
*International applicants may need to submit additional materials in their application package. See International Students for details.
We provide a welcoming environment for students and support them with tools and mentorship needed to succeed in fast-paced, cutting-edge interdisciplinary fields.