MSc Program in Applied Mathematics & Statistics


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Application forms and information concerning the application process can be found on the Graduate Studies website.

If you would like more information, please contact us directly at Department of Mathematics and Statistics, Acadia University, Wolfville, NS  B4P 2R6.  Our email address is




This program offers an exciting opportunity
for students to earn a Masters degree while
gaining experience working and researching
in industry. Students will take courses that
will both prepare them for a work internship
and help them write a MSc thesis. Students
may also spend up to eight months at a
work internship gaining valuable experience
in industry. They will then return to Acadia to
complete a thesis, usually to be based on
the research they completed during their

What makes this program so exciting for
prospective students is the wide range of
research that faculty at Acadia pursue. In
our department, you can pursue research
into a game of cops and robbers,  unbreakable codes, tidal energy in the Bay of Fundy, fractal images, improving medicines, job scheduling, statistical learning and big data, and an optical computer.


Associated with the department is Acadia’s Centre for Mathematical Modelling and Computation (ACMMaC). The focus of ACMMaC is to apply mathematical and statistical models to problems in other fields, industry and the community. Graduate students in our program will have access to ACMMaC resources have the opportunity to become active participants in high-performance computing research.

A HPC cluster and several connected servers support computing needs within the department and in related departments across campus. Acadia is also a member of the ACEnet HPC consortium.


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Faculty Research

The faculty in our department are involved in a wide range of research. Brief summaries are below and more detailed descriptions can be found on the faculty members homepages.

Paul Cabilio:  Nonparametric statistical inference, rank-based methods, incomplete data, statistical modeling 

Hugh Chipman:  Tree models, variable selection, Bayesian methodology, data mining

Nancy Clarke:  Graph theory, combinatorics, design theory and game theory

Eva Curry:  Digital representations for vectors and connections to wavelet theory, iterated function systems, probability, and number theory

Jeff Hooper Algebraic number theory, cryptography

Richard Karsten:  Models of ocean circulation, climate modelling

Wilson Lu:  Survey sampling, replication methods, survey confidentiality, computer experiment design

Franklin Mendivil:  Image processing, stochastic optimization, fractal analysis

Jianan Peng:  Order restricted inference, multiple comparisons, nonparametric statistics

Pritam Ranjan:  Computer experiments, sequential designs, combinatorial designs

Paul Stephenson:  Machine scheduling, optimization algorithms

Holger Teismann:  PDE, control theory, non-linear optics

Ying Zhang:  Statistical computing, time series analysis, applied statistical modelling