Applied Modelling and Quantitative Methods M.Sc.
Applied Modelling and Quantitative Methods is an interdisciplinary program which provides for study towards an M.Sc. or M.A. degree in the application of techniques and theory of modelling in the natural sciences and social sciences. It encompasses the following traditional disciplines: Biology, Business Administration, Chemistry, Computer Science, Economics, Geography, Humanities, Mathematics, Philosophy, Physics & Astronomy and Psychology. The program is designed to overcome some of the barriers to interdisciplinary collaboration by bringing together, at the graduate level, students who are actively applying modelling techniques in their thesis research in a broad range of disciplines. The research is in the social and natural sciences, and in fields in which Trent has demonstrated strong research performance. Although it is oriented towards quantitative models, utilizing computational, mathematical or statistical techniques, it is discipline-based and is not a program in applied mathematics.
There are three primary objectives:
- The teaching of fundamental and common analytical modelling techniques required for research in a large number of quantitative fields.
- The cross-fertilization that comes from sharing ideas with researchers in other disciplines, and the development of the communication skills required for this to occur.
- Sufficient training of the student in his/ her chosen discipline, including coursework and a research thesis, to permit progression to a disciplinary Ph.D. program at another institution.
Students are involved both in thesis research and course work in their "home" discipline, and in interdisciplinary study. They carry out coursework in the foundations and methods of quantitative modelling and participate in an interdisciplinary seminar. In this seminar the student discusses, in a way comprehensible to the audience, the system being modelled, the model developed, and the means of validation of the model; here the emphasis is upon the modelling process itself rather than on the relevance of the results to the discipline of the research. Through this seminar the students develop the skills required to communicate with researchers outside their own discipline, and develop a perspective on their own and other disciplines not obtainable from within a single-discipline context.
The Trent Advantage
- Collaborate on individualized, interdisciplinary research with faculty members in a wide range of disciplines
- Thesis or course-based streams available
- Build a solid foundation of modelling skills that allows you to move on to a PhD program in your home discipline (thesis stream) or focus on Financial Analytics or Big Data Analytics (course stream)
- Full time or part time with flexible start dates (January, May or September)