Field(s) of Specialization
Faculty and Administraton
Dean
Peter Berg
Faculty of Mathematics and Science
Associate Dean
Melanie Pilkington
Faculty of Mathematics and Science
Core Faculty
Professors
S. Ejaz Ahmed, Stephen Anco, Chantal Buteau, Hichem Ben-El-Mechaiekh, Henryk Fuks, Omar Kihel, Yuanlin Li, Alexander Odesskii, Jan Vrbik, Thomas Wolf, Xiaojian Xu
Associate Professor
William Marshall
Assistant Professors
Tianyu Guan, Dongchen Li, Pouria Ramazi
Participating Faculty
Adjunct Professor
Vladimir Sokolov (Landau Institute)
Professors Emeriti
Howard Bell, Mei Ling Huang, Ronald Kerman, Eric Muller
Graduate Program Director
Stephen Anco
sanco@brocku.ca
Graduate Administrative Coordinator
Elena Genkin
905-688-5550, extension 3115
Mackenzie Chown D473
fmsgradoffice@brocku.ca
Administrative Assistant
Alan Liu
905-688-5550, extension 3300
Mackenzie Chown J415
mathstats@brocku.ca
Program Description
The MSc program aims to provide students with an intensive advanced education in areas of Mathematics and Statistics in preparation for doctoral studies or the job market. Students will choose a specialization in either Mathematics or Statistics. The MSc program is designed to normally be completed in six terms or twenty-four months. However, completion in twelve months is possible in Statistics specialization.
The Mathematics specialization provides students with advanced training in areas of active research and current applicability in algebra and number theory, computer algebra algorithms, discrete mathematics and graph theory, dynamical systems, partial differential equations, functional analysis, mathematical music theory, mathematics education, mathematical physics, solitons and integrable systems, topology, and (as a bridge with the Statistics specialization) probability theory and stochastic processes.
The Statistics specialization provides students with solid training in both advanced and applied statistical areas including design of experiment, optimal design for regression, sampling theory, parametric and nonparametric statistical inferences, multivariate statistics, survival analysis and risk models, robust methods, and computational statistics.
The program offers two options: a thesis option (intended normally for students planning to pursue doctoral studies) and a project option (intended normally for those planning to join the job market). The paper for the project option will be based on a research project of a practical nature and must demonstrate a capacity for synthesis and understanding of concepts and techniques related to a specific topic.
Each student will consult with their Supervisor when planning a program of study and choosing courses and must receive approval from the Graduate Program Director.
Field(s) of Specialization
Participating faculty are engaged in active research in the following areas of specialization:
Mathematics
- Algebraic number theory
- Cellular automata, discrete dynamical systems and complex networks
- Combinatorial and additive number theory
- Computational methods for solving algebraic and differential systems
- Cryptography
- Geometric curve flows
- Graph theory and algorithmic game theory
- Group and ring theory
- High performance parallel computing
- Mathematical music theory
- Mathematical physics and general relativity
- Mathematics education
- Nonlinear functional analysis and applications to optimization, game theory, mathematical economics, and differential systems
- Solitons and integrability of partial differential equations
- Symmetry analysis and computer algebra applied to nonlinear differential equations
Statistics
- Nonparametric statistical inference theory and methods
- Extreme value theory and applications
- Quantile regression method and applications
- Experimental design and regression theory and methods
- Applied probability, stochastic models and queueing network
- Survival analysis and risk models
- Probability distribution theory and applications
- Monte Carlo simulations and resampling techniques
- Multivariate analysis
- Accelerated life testing
- Linear, generalized linear, and nonlinear models
- Robust statistics
- Computational methods and applications to stochastic models
- Convergence and efficiency of Markov chain Monte Carlo algorithms
- Optimal design of experiments
Facilities
- Each graduate student will be provided with personal desk space and a desktop PC linked to the university network system.
- Graduate students will have access to the Mathematics computer lab as well as to computer labs located in the vicinity of the Department of Mathematics and Statistics. Software includes a wide array of both commercial and open source applications for supporting research in mathematics and statistics.
- Brock is also a full member of the SHARCNET consortium with access to all its high performance clusters of powerful workstations and vast storage resources.
Admission Requirements
- Successful completion of four year Bachelor’s degree, or equivalent, in Mathematics or Statistics, or a related field, with an average of not less than B+.
- Agreement from a faculty advisor to supervise the student is required for admission to the program.
- The Graduate Admissions Committee will review all applications and recommend admission for a limited number of candidates.
- Those lacking sufficient background preparation may be required to complete a qualifying term or year to upgrade their applications. Completion of a qualifying term or year does not guarantee acceptance into the program.
- Part-time study is available.
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