Modelling and Computational Science
The Faculty of Science, in collaboration with the School of Energy Systems and Nuclear Science, offers graduate programs leading to the degrees of Master of Science or Doctor of Philosophy in Modelling and Computational Science.
Students have the option of obtaining their degree through a thesis option or a course-based option. The thesis option combines course-based learning with the writing of a thesis that may involve original contributions to research, while the course-based option has an increased emphasis on course-based learning, and the development of research skills is achieved through the writing of a Research Report. The expected time for degree completion is 20 months.
The PhD program focuses on applied research with the aim of producing highly trained researchers for industry and academia. Students will obtain their degree through a combination of advanced course work, independent research, research seminars, workshops, peer-reviewed publications and a research dissertation. The expected time to completion is 48 months starting in January, May or September.
The objectives of these programs are to provide opportunities for students to acquire the following:
- Knowledge and skills in the modelling of real-world phenomena;
- Knowledge and skills in computational science and computer programming;
- Scientific communication skills;
- Preparation for PhD studies (MSc);
- Preparation for a career in research, either in academia or industry (PhD); and
- Preparation for the job market.
UOIT is in a unique position to offer this program. By its nature, modelling and computational science are interdisciplinary, requiring commitment from core faculty members from many different disciplines, and whose research itself is interdisciplinary. Not only do the core faculty of the graduate programs in Modelling and Computational Science satisfy this requirement, but the faculties at UOIT are themselves single interdisciplinary units. The Faculty of Science has no traditional departments, fostering interdisciplinary collaboration.
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