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Modelling and Computational Science, PhD


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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 Doctor of Philosophy (PhD) program in Modelling and Computational Science take 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 PhD program are in an excellent position to fill these positions and to contribute to the province’s and the country’s economy. Graduates of the PhD program will have the possibility of continuing their career at the post-doctoral level and eventually obtaining an academic position in a unit corresponding to their research expertise. 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.

The PhD program is comprised of two fields:

  • Computational Physical Sciences
  • Scientific Computing

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

 

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

 

Admissions requirements


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

The minimum admission requirement for the PhD program is completion of an MSc-level degree in science, engineering or a related area from a Canadian university or its equivalent.

Prior to being accepted into the program, PhD applicants must be accepted by a professor who specializes in their desired area of research and who is willing to act as a supervisor.

Under exceptional circumstances, MSc in Modelling and Computational Science students may transfer to the PhD program after completing one academic year in the MSc program if the following conditions are met:

  1. Completion of a full master’s program of course work (six courses worth a total of 18 credits), with at least an A-minus average.
  2. Strong evidence of research ability.
  3. Approval of the transfer by the research supervisor(s) and the supervisory committee. The transfer must also be approved by the graduate program director and the Dean of Graduate Studies.

See the university’s policy on transferring from a thesis-based master’s to a PhD program  for additional information.

Part-time studies


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

Degree requirements


Students in the PhD program must successfully complete at least three courses. As part of the residency requirement, two of the courses must be taken at the university. At least one course must be a 7000-level course.

All PhD students must demonstrate a broad knowledge of Modelling and Computational Science. This is normally demonstrated through the completion of an appropriate set of courses at the graduate level. To satisfy the breadth requirement, the student must successfully complete courses on three out of the following four topics:

  • Mathematical Modelling, following the calendar description of MCSC 6010G .
  • Numerical Analysis, following the calendar description of MCSC 6020G .
  • High-Performance Computing, following the calendar description of MCSC 6030G .
  • Modeling and Simulating Systems using Discrete Units, following the calendar description of MCSC 6040G .

When a student is admitted to the PhD, the Graduate Admissions Committee of the program, together with the research supervisor, evaluates the courses from their previous degrees to determine which courses count towards the breadth requirement and identify the areas in which an additional course is required.

Students who enter the PhD from the Modelling and Computational Science MSc program without completing the latter will be required to take three courses in addition to those taken in the MSc.

In addition to the above requirements, students must successfully complete MCSC 7000G - Modelling and Computational Science Professional Skills , pass the PhD candidacy examination (MCSC 7001G - PhD Thesis Proposal and Candidacy Exam ) and prepare and orally defend their doctoral dissertation (MCSC 7003G - PhD Dissertation ).

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