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Trent University
Applied Modelling & Quantitative Methods
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  1. Trentu.ca
  2. Applied Modelling & Quantitative Methods
  3. Program
  4. Thesis M.A./M.Sc.

Thesis M.A./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.

Degree Requirements

  • Students are normally required to take AMOD 5210H, 5310H, 5320H and one of 5220H, 5230H or 5240H, in addition to the two seminar courses AMOD 5901H and 5902H.
  • Candidates are required to submit and be examined on a research thesis supervised by a core faculty member.  Selection of the research topic is made by the student together with her/his supervisor and graduate supervisory committee (typically two or three core faculty members including the supervisor).

The Trent Advantage 

  • Collaborate on individualized, interdisciplinary research with faculty members in a wide range of disciplines
  • Build a solid foundation of modelling skills that allows you to move on to a PhD program in your home discipline (thesis stream)
  • Full time or part time with flexible start dates (January, May or September)

M.Sc. or M.A.

  • M.Sc. or M.A.
  • Big Data Analytics M.SC.
  • Big Data Financial Analytics M.SC.
  • Data Science and Analytics M.SC.
  • Course Listing
  • Admission Requirements
  • AMOD Alumni
  • Employment Opportunities
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