We are always interested in hearing from potential students. We generally look for people with skills or interests in bioinformatics, or related disciplines such as mathematical/computational biology, machine learning, and statistics. Our lab offers excellent opportunities for candidates to identify and solve fundamental computational and mathematical problems in data analysis and modelling, and to hone their skills in the latest techniques in these areas, while simultaneously helping to advance research in cancer, stem cells and molecular biology. The students would likely be accepted through one of the degree programs offered by the School of Electrical Engineering and Computer Science, the Department of Biochemistry, Microbiology and Immunology, or the Department of Cellular and Molecular Medicine, although other degree programs may be possible. Those interested should contact Dr. Perkins at firstname.lastname@example.org. We receive many inquiries and cannot promise a response, but we do our best.
Why join the lab?
Our lab is uniquely interdisciplinary and collaborative. We are a computational lab, specializing in bioinformatics, computational biology, machine learning, and mathematical biology. However, we are located at the Ottawa Hospital Research Institute, where we are surrounded by wetlab and clinical researchers. The lab is also adjacent to StemCore, the high-throughput genomics facility of the institute, which provides services such as next generation sequencing (Solexa), microarray expression profiling, FACS, etc. Thus, our environment is data-rich, ripe with opportunities for collaborations, and provides a constant stream of new and stimulating computational problems to work on.
On the wetlab side, example collaborations involve the genetic regulation of stem cell function, especially in embryonic stem cells (with B. Stanford), blood stem cells (with M. Brand), and in skeletal muscle (with M. Rudnicki), in gene regulation in yeast and other microorganisms (with M. Kaern and P. Swain), in cancer cell motility (with J. Lee), and in the optimization of oncolytic viruses (with J. Bell). In these areas, our efforts tends towards modeling, advanced/integrative data analysis, and attempts to identify "organizing principles" of the systems we study. We also do pure computational and mathematical research. On the computational side, problems surrounding stochastic chemical kinetic models are a strong interest of the past few years. On the more mathematical side, recent interests include design of pooling strategies for high-throughput screening (with E. Brown and D. Precup) and scaling laws for complex, probabilistic dynamical systems (with L. Glass and R. Edwards).
What background do you need?
We are interested in students from a variety of backgrounds. Ideally, you should be skilled in at least one of: computer science (especially machine learning, bioinformatics or computational biology), mathematics (especially mathematical biology or nonlinear dynamics), physics, or statistics. Students from more biology or biochemistry backgrounds may also be considered. There are many opportunities for different types of research in the lab, and our belief is that when students or fellows bring good skills to the lab, good science will result.
What to do next?
If you think you might be interested in joining the lab, please contact Dr. Perkins by email at email@example.com.