- Sean Bohun, BSc, MSc, PhD
- Jeremy Bradbury, BSc, MSc, PhD
- Pietro-Luciano Buono, BSc, MSc, PhD
- Anatoli Chkrebtii, BSc, MSc, PhD
- Jason Cole, MSc, PhD
- Christopher Collins, BSc, MSc, PhD
- Greg Crawford, BSc, MSc, PhD, MPA
- Hendrick de Haan, BSc, PhD
- Mehran Ebrahimi, BEng, MSc, PhD
- Mark Green, BSc, MSc, PhD
- Huaxiong Huang, BSc, PhD
- Salma Karray, PhD
- William Langford, BSc, PhD
- Greg Lewis, BSc, MSc, PhD
- Fletcher Lu, BMath, MMath, PhD
- Lixuan Lu, BES, MES, PhD
- Fedor Naumkin, MSc, PhD
- Eleodor Nichita, BSc, MSc, PhD
- Ken Pu, BASc, MASc, PhD
- Faisal Qureshi, BSc, MSc, PhD
- Karthik Sankaranarayanan, MSc, PhD
- William Smith, BASc, MSc, MASc, PhD, PEng
- Mark Staley, BSc, MSc, PhD
- Chirag Surti, MSc, PhD
- Isaac Tamblyn, PhD
- Lennaert van Veen, MSc, PhD
- Anthony Waker, BSc, PhD
- Ed Waller, BSc, MScE, PhD
- Elysa Widjaja, MBBS, MRCP, FRCR, MD, MPH
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) and Doctor of Philosophy (PhD) programs 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. UOIT’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 and PhD programs 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. 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
1 McAteer, H. Filling the Gaps: Recruitment and Retention of Top Talent in Canada, the Conference Board of Canada, August 2015.
In addition to the general admission requirements for graduate studies at UOIT , Modelling and Computational Science applicants must meet the following program-specific requirements.
MSc in Modelling and Computational Science
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.
PhD in Modelling and Computational Science
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:
- 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.
- Strong evidence of research ability.
- 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 UOIT’s policy on transferring from a thesis-based master’s to a PhD program for additional information.
Part-time studies are permitted on a case-by-case basis.
Select a program from the list below for details on degree requirements.