Queen's University

School of

Graduate Studies

School of

Graduate Studies

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Mathematical Engineering


"The Mathematics and Engineering graduate program at Queen's University is truly one of a kind, offering a unique mathematical perspective on engineering and applied science and preparing students for a range of careers, from academia to industry. The quality of research at Queen's is exceptional, and the superb instruction and range of courses offered provide for a great learning and working environment. The program provided me with a strong mathematical background, which I have found invaluable for investigating real world engineering and applied science problems.
I have had experience in both academia and industry, and have consistently found my experience at Queen's indispensable.

Jeff Calder, MSc 2010

Program Contact

Jennifer Read
Graduate Assistant
Department of Mathematics & Statistics
Queen's University
Kingston, ON, Canada K7L 3N6

Phone: 613.533.2405
E-mail: gradapp@mast.queensu.ca
Website: www.mast.queensu.ca


Program Overview

The combined programs in Mathematics and Engineering are ideally suited for students interested in a mathematical perspective on engineering. Students may enrol through either the Faculty of Engineering & Applied Science or the Faculty of Arts and Science. Students enrolling through the Faculty of Applied Science, while receiving their degree from the Department of Mathematics and Statistics, will receive an Engineering graduate degree, and so will have the same career options available to them as graduates from standard Engineering graduate programmes. Graduate students in Mathematics and Engineering come from a variety of backgrounds: mathematics; applied mathematics; electrical engineering; mechanical engineering.

See "Why Grad Studies" videos by Queen's Engineering faculty and students


Many areas of engineering benefit greatly from their interaction with Mathematics and/or Statistics. Thus the presence of an Engineering group in the Department of Mathematics and Statistics is natural.

Career paths – employment opportunities

Graduates from the Mathematics and Engineering programs have gone on to rewarding careers in industry, finance and academia.

Degrees Offered/Method of Completion

Degrees Offered

M.Sc.: 18-24 months

M.A.Sc.: 18-24 months

Ph.D.: 4 years

Method of Completion

M.Sc. Pattern I & M.A.Sc.: Course work and a research thesis

M.Sc. Pattern II.: Course work and research project

Ph.D.: Course work, comprehensive exam and research thesis

Fields of study and Supervisors

Research in Mathematics and Engineering and Applied Mathematics takes place in the broad areas of communication and information theory, control theory, signal processing and various fields in applied mathematics. It is extremely important to contact potential supervisors in advance. In most cases students will receive funding from their research supervisor and so the support of a supervisor is crucial for gaining admission.

Selim Akl - akl@cs.queensu.ca
Design and Analysis of Algorithms, Parallel Computing, Biomedical Computing, Unconventional Computation

Fady Alajaji - fady@mast.queensu.ca
Information and communication theory, data compression, joint source-channel coding, error control codes

Gunnar Blohm - gunnar.blohm@queensu.ca
Artificial neural networks, Neuronal spike coding, Clifford algebra (dual quaternions), Bayesian statistics, Systems identification and control theory, Large-scale spiking neuronal models, Sensory-motor neuroscience

Steven Blostein - steven.blostein@queensu.ca
Signal processing for communications, wireless communications, detection and estimation theory

Saeed Gazor - gazor@queensu.ca
Signal Processing, Adaptive filters, Array Signal Processing, Speech Processing, Image Processing, Wireless Communication Systems, Information Theory

Bahman Gharesifard - bahman@mast.queensu.ca
Distributed optimization and control, game theory, learning, geometric control theory

Mark Green - greenm@civil.queensu.ca
Bridge-vehicle dynamics, repair of structures with fibre reinforced polymer (FRP) materials, prestressing applications of FRP materials, fire resistance of structures, smart and adaptive materials for structures, control of structural vibrations

Martin Guay - martin.guay@chee.queensu.ca
Control theory, Process Control, Applied Statistics

Andrew Lewis - andrew@mast.queensu.ca
Geometric mechanics, geometric control theory

Tamas Linder - linder@mast.queensu.ca
Communications, source/channel coding, data compression,  information theory; statistical pattern recognition

Abdol-Reza Mansouri - mansouri@mast.queensu.ca
Nonlinear control theory, image processing

Jim McLellan - james.mclellan@queensu.ca
Nonlinear control, modelling of nonlinear chemical processes, measures of nonlinearity

Andrew Pollard - pollard@me.queensu.ca
Turbulence and fluid dynamics, numerical analysis, high performance computing

Glen Takahara - takahara@mast.queensu.ca
Communication theory, communication networks, queueing theory

David Thomson - djt@mast.queensu.ca
Solar oscillations and space physics, cellular phone systems, signal processing, special functions

Serdar Yuksel  - yuksel@mast.queensu.ca
Stochastic and decentralized control, information theory,  applied probability

Funding, Academic Prerequisites & Deadline

Funding Information

M.Sc. & M.A.Sc.: Up to $21,750 a year

Ph.D.: $21,750 minimum per year funding packages can consist of teaching and/or research assistantships, internal and external awards. We encourage all applicants to apply for support through external granting agencies.

Academic Prerequisites

Master’s programs: 4 year Bachelor’s degree (Honours preferred) with a minimum B+ average in the third and fourth years.

Doctoral program: Master’s degree with a minimum B+ average in all courses, demonstrated research potential and clear interests.

NB: Applicants applying to complete their degree through the Faculty of Engineering & Applied Science should normally have an undergraduate engineering degree.

Application Requirements

In addition to completing an application form and providing transcripts and letters of recommendation applicants are asked to provide the following:

  • List of relevant courses taken. Provide a description of the courses taken in mathematics, statistics, or related areas in the third year and beyond. The list should include titles and authors of textbooks used and chapters/topics covered.
  • Sample of written work. Applicants to the doctoral program should submit a copy of the abstract of their Master’s thesis. Applicants to a Master’s program should submit a copy of their fourth year thesis or project, if applicable.

Test Requirements

Those applicants whose native languages do not include English will be required to obtain a satisfactory standing in an English Language Proficiency Test as part of the application process.

Key Dates and Deadlines

Application Deadline: There is no deadline to apply for admission, but applicants are encouraged to apply early in order to receive full consideration for financial support


Learning Outcomes

Degree Level Expectations - MASc (89 KB)

Degree Level Expectations - PhD (87 KB)