Modelling and Computational Science, MSc

General information

Mathematical modelling is an important tool in the study of physical and biological phenomena. The field of computational science combines the implementation of mathematical models, computer algorithms and knowledge in a particular area of application in order to provide an additional tool for the study of phenomena and, in particular, to facilitate the study of problems that are intractable or difficult to study using other approaches. Mathematical models and computational science are powerful methods to study problems such as atmospheric phenomena; climate variability; molecular behaviour of matter; protein folding; option pricing in financial markets; and many other physical, biological, medical, environmental and economic problems.

The Master of Science (MSc) program in Modelling and Computational Science takes advantage of the interdisciplinary nature of the Faculty of Science and collaborating faculties to offer students a program of study that introduces them to all aspects of the modelling process. The university’s membership in the Shared Hierarchical Research Computer Network (SHARCNET), the Southern Ontario Smart Computing Innovation Platform (SOSCIP) and the advanced local computing infrastructure provides access to state-of-the-art computational facilities.

Part of the motivation for the establishment of the program stemmed from a number of surveys by professional organizations and business alliances reporting a critical need for highly qualified personnel (HQP) with skills in high-performance computing and modern applied mathematics. A recent survey by the Conference Board of Canada confirms that this is still the case. Well over half of the queried companies in science, IT and high technology reported significant trouble in recruiting talent1. Moreover, Ontario is reported to have the greatest shortage of HQP1. The jobs in these areas are expected to be within interdisciplinary groups that perform a number of different interrelated tasks. Thus, problem-solving skills and the ability to communicate and work with people from a variety of disciplines and manage big, collaborative software development projects are quintessential.

Graduates of the MSc program are in an excellent position to fill these positions and to contribute to the province’s and the country’s economy. Depending on the background of the student, successful completion of the MSc in Modelling and Computational Science also prepares the student to enter PhD programs in applied mathematics, physics, chemistry and engineering. They will also be highly qualified to obtain positions as career scientists in a variety of institutions, whether at the governmental level or in the industrial, business or financial sectors.

1 McAteer, H. Filling the Gaps: Recruitment and Retention of Top Talent in Canada, the Conference Board of Canada, August 2015.

Admission requirements

In addition to the general admission requirements for graduate studies , Modelling and Computational Science applicants must meet the following program-specific requirements.

Hold an honours undergraduate degree in mathematics, science or engineering. At a minimum, applicants must be acquainted with basic numerical methods, linear algebra, differential equations and possess some computing skills. To assist with the assessment of the application, applicants should submit detailed descriptions of any completed courses in these areas. Course descriptions should be copied from the university’s academic calendar.

Admission depends on the availability of a research supervisor. Applicants should contact the potential supervisor and/or the graduate program director before formally applying.

A current list of graduate faculty is available on the Faculty of Science’s website.

Part-time studies

Part-time studies are permitted on a case-by-case basis.

Degree requirements

For the MSc course-based option, students must successfully complete 30 credits, including eight 3-credit courses and the 6-credit MCSC 6002G - MSc Research Project . For the MSc thesis-based option, students must also successfully complete 30 credits, including five 3-credit courses and a 15-credit thesis. The eight 3-credit courses for the course-based option and the five 3-credit courses for the thesis option must include at least three of the following:

• MCSC 6010G - Mathematical Modelling  
• MCSC 6020G - Numerical Analysis  
• MCSC 6030G - High-Performance Computing  
• MCSC 6040G - Modeling and Simulating Systems using Discrete Units  

A minimum grade of B-minus must be achieved in each course. No more than two elective courses may be fourth-year undergraduate courses not included in the list of graduate course electives. All courses taken must be approved in advance by the student’s supervisory committee. In addition to the eight courses and the research project for the course-based option, students must also successfully complete the non-credit courses  MCSC 6000G - Graduate Seminar in Modelling and Computational Science  and MCSC 6003G - Modelling and Computational Science Professional Skills . For the thesis-based option, students must also successfully complete the non-credit courses MCSC 6000G - Graduate Seminar in Modelling and Computational Science , MCSC 6003G - Modelling and Computational Science Professional Skills  and the 15-credit MCSC 6001G - MSc Thesis  . The latter is evaluated by an examining committee and involves an oral presentation.

Suggested progression through program

Thesis-based option

Course listing