Computational Science & Engineering

M.Sc, M.A.Sc, Ph.D

Queen's is one of the first universities in Canada to launch a university-wide specialization in computational science and engineering, giving graduates a head start in fields such as drug discovery, behavioural science, genomics, mathematical economics, digital imaging and nanotechnology, just to name a few. Computational science is already facilitating major advances in many disciplines and is poised to make significant contributions to society as a whole.

The Queen's Collaborative Graduate Program in Computational Science and Engineering connects today's databases, algorithms, simulations and information systems with tomorrow's scientific breakthroughs. It's an exciting, fulfilling option for students looking to get even more out of an existing degree.

Designed to enhance the value of your master's degree, this new three-course specialization teaches you the latest methods for applying the power of high-performance computing to scientific problems in your area of study. From advanced numerical analysis, mathematical modelling and simulation, and parallel programming, these methods support and enhance more traditional approaches based on theory and experimentation

The tools of computational science allow researchers to tackle complex questions that might otherwise be overwhelming or out of reach. Every day more and more academic disciplines are finding ways to capitalize on the speed and efficiency of computation, so we welcome students not only from engineering, physical science and life science, but also from business, social science and the humanities.

As the central site of one of North America's best high-performance computing facilities, Queen's is ideally equipped to offer this program. The High Performance Computing Virtual Laboratory, a consortium of five Ontario universities, offers students a world-class environment for computational science research and education.

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Degrees Offered / Length of Program

• M.Sc. & M.A.Sc. (specialising in computational science & engineering)

Method of Completion

 In the Collaborative Graduate Program in Computational Science and Engineering, you must:

Collaborate with the Best

Participating Programs are Biochemistry; Biology, Chemical Engineering; Chemistry; Civil Engineering; Community Health and Epidemiology, Computing and Information Science; Economics; Electrical and Computer Engineering; Geography; Geological Sciences and Geological Engineering; Mathematics and Statistics; Mechanical and Materials Engineering; Mining Engineering; Neuroscience, Physics; and Psychology.

This is a unique opportunity to get the best of both worlds: the rewards of in-depth study in your chosen discipline and the excitement of learning new, highly relevant computational skills. We created the course-based specialization for talented, dedicated students capable of maintaining intense focus in their specialty while applying newly acquired computational science knowledge directly to their individual research. It's a chance to expand your academic horizons by regularly stepping beyond the borders of your home department, without disrupting your course of study.

The program is inherently collaborative, bringing together some of the university's top teachers and researchers from diverse scientific disciplines; often the only thing they have in common is their dedication to discovering new and better computational techniques. As a student in the program, you'll be exposed to the wide-ranging expertise of this multidisciplinary team of faculty. Even your classmates will be from a variety of academic backgrounds. Being a member of this eclectic scholarly community will fuel your intellectual curiosity and enrich your academic experience.

Employment Opportunities

High-performance computing skills are becoming a prerequisite for success in an increasing number of careers within academe and industry. Students who accept the challenge of the Queen's Collaborative Graduate Program in Computational Science and Engineering tackle complex research questions in their fields using leading-edge computing algorithms and architectures.

Funding Information

All students in the program will be considered for funding support in accordance with their respective home program's
funding policy. Students are also encouraged to apply for external scholarships such as Ontario Graduate Scholarships, CIHR, NSERC, or SSHRC studentships

 

Academic Prerequisites

The program is available to masters students associated with participating departments. Students must first be admitted to the graduate program in a participating department and must meet the specific requirements of that departmental program. Students interested in completing the specialization should contact the Graduate Coordinator in their "home" department and complete an enrolment form.

Profiles

• Prof Andrew Pollard - work hard on research, but consider its implications too...