Students
Tuition Fee
Not Available
Start Date
2026-09-01
Medium of studying
Not Available
Duration
Not Available
Details
Program Details
Degree
Bachelors
Major
Applied Mathematics | Mathematics | Statistics
Area of study
Mathematics and Statistics
Course Language
English
Intakes
Program start dateApplication deadline
2025-09-01-
2025-12-01-
2026-09-01-
2026-12-01-
2027-09-01-
2027-12-01-
About Program

Program Overview


Advanced Research Project

The Advanced Research Project, denoted as MATH/STAT*4600, offers undergraduate students the opportunity to engage in mathematics and statistics research projects under the supervision of faculty members each semester. This project provides a unique chance for students to work on advanced topics that align with their interests and academic goals.


Program Structure

  • The project is available as a 1.00 credit course, offered in both the Fall and Winter semesters.
  • Students can register for either MATH4600 or STAT4600, depending on their research focus.

Research Opportunities

  • Faculty members are available for supervision, with specific research areas including:
    • Mathematics of two-dimensional turbulence (Dr. Geordie Richards)
    • Exploring Variable and Model Selection Techniques for Multinomial Response Data (Dr. Nagham Mohammad)
    • Spatial-temporal models, Bayesian statistics, time series, and applications to epidemiology (Dr. Justin Slater)
  • Additional research opportunities may be available by contacting faculty members not listed, to inquire about potential projects.

Semester-Specific Research Projects

Fall 2025

  • MATH*4600: Mathematics of two-dimensional turbulence, supervised by Dr. Geordie Richards.

Winter 2026

  • MATH*4600:
    • Mathematics of two-dimensional turbulence, supervised by Dr. Geordie Richards.
    • A project supervised by Dr. Matthew Demers, with details available upon request.
  • STAT*4600:
    • Exploring Variable and Model Selection Techniques for Multinomial Response Data, supervised by Dr. Nagham Mohammad.
    • Spatial-temporal models, Bayesian statistics, time series, and applications to epidemiology, supervised by Dr. Justin Slater.
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