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PhD Program Requirements

Students in the Doctor of Philosophy (PhD) program can conduct research in the fields of 1) Statistical Theory and Applications or 2) Probability or 3) Actuarial Science and Mathematical Finance.

The research conducted in the department is vast and covers a diverse set of areas in theoretical and applied aspects of Statistical Sciences. Students have the opportunity to work in multidisciplinary areas and team up with researchers in, for example, Biostatistics, Computer Science, Economics, Engineering, and the Rotman School of Management.

The main purpose of the program is to prepare students for pursuing advanced research both in academia and in research institutes.

Applicants may enter the PhD program via one of two routes: 1) following completion of an appropriate master’s degree or 2) direct entry after completing an appropriate bachelor’s degree (excluding Actuarial Science and Mathematical Finance).

Program Length

This full-time program normally takes 12 academic sessions (four years) to complete and requires continuous registration. There is a maximum time limit of six years to complete the program.

PhD Direct Entry

This full-time program   normally takes 15 academic sessions (five years) to complete and requires continuous registration. There is a maximum time limit of seven years to complete the program .

Course Requirements

During Year 1, students must successfully complete a total of 3.0 full-course equivalents (FCEs) as follows:

• STA3000Y Advanced Theory of Statistics (1.0 FCE)

And two of the following:

• STA2101H Methods of Applied Statistics I and STA2201H Methods of Applied Statistics II
• STA2111H Probability Theory I and STA2211H Probability Theory II
• STA2311H Advanced Computational Methods for Statistics I and STA2312H Advanced Computational Methods for Statistics II.

Courses must be chosen in consultation with the advisor and approved by the Associate Chair of Graduate Studies.

Students must complete an additional 2.0 full-course equivalents (FCEs) at the graduate level. The additional courses must be approved by the Associate Chair of Graduate Studies.  It is strongly recommended that these courses are completed at the end of Year 2, but no later than the end of Year 4.

Field: Actuarial Science and Mathematical Finance

During Year 1, students must complete the following 3.0 full-course equivalents (FCEs) :

• STA2111H Probability Theory I,
• STA2211H Probability Theory II, and
• STA2503H Applied Probability for Mathematical Finance.
• STA2501H Advanced Topics in Actuarial Science or
• STA4246H Research Topics in Mathematical Finance.
• STA2101H Methods of Applied Statistics I and STA2201H Methods of Applied Statistics II or
• STA2311H Advanced Computational Methods for Statistics I and STA2312H Advanced Computational Methods for Statistics II or
• STA3000Y Advanced Theory of Statistics.

Comprehensive Examination Requirements

Within Years 1 and 2, students must complete a two-part comprehensive examination: 1) an in-class written comprehensive exam and 2) a research comprehensive exam. Students must pass both the in-class written exam and the research exam to continue in the program.

In-Class Written Exam

Students must attempt the in-class written comprehensive exam by the end of Year 1. If a student fails this portion of the comprehensive exam, one further attempt will be allowed by the end of Year 2. Students who achieve A or A+ grades in all required coursework are exempt from the in-class written exam.

Research Comprehensive Exam

Students must attempt the research comprehensive exam by the beginning of Year 2, which includes a technical report and an oral presentation. If a student fails this portion of the comprehensive exam, one further attempt will be allowed at the end of Year 2.

Thesis Requirements

Conducting original research is the most important part of doctoral work. Your thesis must constitute significant and original contribution to the field.

Annual Doctoral Progress

You will have yearly meetings with a committee of no less than three faculty members to assess your progress.   

Departmental Oral Examination and Final Oral Examination

The completed thesis must be presented and defended within the Department of Statistical Sciences in addition to being presented and defended at the School of Graduate Studies (SGS).  

Residency Requirements

All students must satisfy a two-year residency requirement as outlined in the Calendar of the School of Graduate Studies, General Regulations .

Direct-Entry PhD students must satisfy a three-year residency requirement.

Questions about your program?  

Please reach out to our graduate team at [email protected] . 

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Doctor of Philosophy (PhD)

Graduate studies | Our programs | Doctor of Philosophy

Program Details

Phd in actuarial science, who is this program for.

This program is for students who have completed a Master’s or Bachelor's degree in statistics, actuarial science, mathematics, or other quantitative discipline and would like to pursue research in actuarial science. Graduates from this program typically enter academia or work in the private sector after graduation.

What does it take to get in?

A Master's degree in statistics, actuarial science, mathematics, or other quantitative discipline completed or expected with a cumulative GPA of at least 78% from a Canadian university ( or its equivalent ). A demonstrated ability to conduct high level research is helpful but not required. 

Students with a four-year Bachelor's degree are invited to apply directly to the PhD program. The admissions committee will review each applicant's background for suitability and may recommend admission to our Master's program instead. 

When should I apply?

Priority application deadline: December 15th. Applications must be completed by this date with all documents uploaded to be considered for early admission, invitation to our Grad Visit Day, and entrance awards. 

Final application deadline: January 15 th  for fall admissions (there are no Winter or Spring admissions). 

PhD in Biostatistics

This program is for students who have completed a Master’s or Bachelor's degree in statistics, actuarial science, mathematics, or other quantitative discipline that are looking to develop research skills to address a wide range of challenges arising in health, biology, and the environment. Demand for biostatisticians in Canada and internationally is high and graduates typically find employment in areas such as pharmaceutical companies, contract research organizations, regional or national centers for health research, academic centers, and public health agencies.

PhD in Statistics

This program is for students who have completed a Master’s or Bachelor's degree in statistics, actuarial science, mathematics, or other quantitative discipline. The PhD will build on this background with the goal of training first-class independent researchers. Graduates from this program find career opportunities in academia, research, and private industry.

Research Areas

Actuarial science.

• Capital allocation
• Portfolio optimization
• Pricing and hedging of investment-linked products
• Risk management
• Ruin theory
• Stochastic modelling 
• Monte Carlo and quasi-Monte Carlo

Biostatistics

• Analysis of life history data
• Causal inference
• Clustered data
• Design and analysis of clinical trials
• Epidemiological methods
• Event history analysis
• Generalized linear models
• Longitudinal data analysis
• Methods for dealing with incomplete data and measurement error
• Stochastic processes
• Statistical computing
• Studies of biological systems
• Artificial intelligence
• Business and industrial statistics
• Computational statistics
• Data science
• Exploratory data analysis
• Machine learning
• Non-parametric methods
• Probability theory
• Statistical modeling and inference
• Statistical geometry
• Survey methods
• Survival analysis
• Time series

Additional Information

• Admission and degree requirements
• Course listings
• Actuarial Science faculty members
• Biostatistics faculty members
• Statistics faculty members