Program Description & Requirements

Our PhD strongly emphasises the development of a course of study and research that is customized to each student's background, interests and aptitudes. The graduate student advisory process aims to ensure a focus on individuality as a key to success in research, and the structure of study and course selection in the initial stages of each student's graduate career reflects this.

During the first couple of years of graduate studies, most students take a range of courses from those designated as "core" as well as from more advanced course offerings. With advice and guidance, each student talks a path towards defining her/his own series of courses and research studies. Some students are ready to move ahead to research with a selective menu of courses from the very start; students entering with more advanced preparation (e.g. MS degree or prior research experience) will generally take more advanced courses and proceed more rapidly to thesis research. Other students enter with less advanced preparation and take most of the core courses (3 or 4 per semester) in each of the first two years; this ensures broad and deep foundations in the core of mathematical statistics, stochastic modelling, statistical computation and applied statistics. Students have opportunities to also take courses in other disciplines, as well as to engage in multiple independent and research studies.

Following the Preliminary examination (usually at the end of the second year, or in some cases the fall of the third), students devote most of their time to development of original research, perhaps with a small number of additional advanced courses. Students attend conferences and workshops and present research to the department and scientific community as part of their research education. The PhD is awarded following a successful oral presentation and examination by the thesis committee (the "defense"). Most students complete their PhD within 4 or 5 years.