Master of Science in Applied Modelling and Quantitative Methods M.Sc.
Cross disciplinary boundaries as you explore and apply modelling techniques to your research.
Earn an M.A. or an M.Sc. in the theory of modelling and the application of techniques in the natural sciences or social sciences. Interdisciplinary collaboration is at the core of this program as students with backgrounds in economics and computer science come together with those from math and psychology, and beyond. As you complete your coursework and conduct your research, you will be sharing ideas with classmates from an array of disciplines. Immersed in this multidisciplinary environment, you will develop new perspectives that will position you well for the future.
- Collaborate on individualized, interdisciplinary research with faculty members in a wide range of disciplines.
- Choose from Biology, Business Administration, Chemistry, Computer Science, Economics, Geography, Humanities, Mathematics, Philosophy, Physics & Astronomy and Psychology.
- Build a solid foundation of modelling skills that will allow you to move on to a Ph.D. program in your discipline.
- M.A. or M.Sc.
- Full- or part-time studies
- Thesis-based and course-based programs
- Thesis based program takes 2 years to complete
- January, May, September intake for thesis-based program / September intake for course-based program
- B.A. or B.Sc. honours degree in one of the traditional disciplines: Anthropology, Biology, Business Administration, Chemistry, Computing & Information Systems, Economics, Geography, Humanities, Mathematics, Physics & Astronomy, Philosophy, or Psychology
- Minimum B+ (77%) or equivalent in the work of the last four semesters or the last two undergraduate years (last ten full credits)
- A university course in differential and integral calculus, and one in probability and statistics or the equivalent
- Some familiarity with linear algebra, and be capable of programming at an elementary level in at least one computational language
- A course in either differential equations or advanced statistics is required, depending on whether the student’s area of research will be mathematics or statistics based