Mathematical and statistical modelling approaches are essential in dealing with complex systems whose components interact in a remarkably dynamic manner in a competitive, and uncertain, environment. These systems are ubiquitous in nature, technology, and society. Mathematical and statistical modeling approaches are crucial in traditional disciplines like physical and computer sciences, engineering and technology. Increasingly, they are being applied to a diverse set of emerging applications in health and life sciences, environment and ecology, finance, business and economics, as well as in governance and social systems. Applied modelling enables further progress in critical areas of human endeavour, fundamentally enhancing our well-being.

The interdisciplinary PhD program in Mathematical and Statistical Modelling will serve the growing demand for advanced quantitative skills in Ontario’s knowledge-based economy. Our success in this process lies with a holistic, interdisciplinary approach to problem-solving. Students in this program will develop expertise using the tools of mathematical and statistical modelling. They will carry out independent research while developing additional expertise in one of three domains (1) Health, Environment and Ecology; (2) Finance, Business and Economics; and (3) Complex Systems, Information and Big Data. Graduates of this program will contribute in creative and innovative ways to solving Ontario’s complex interdisciplinary problems.