Intelligent Systems and Data Science (PhD)

The PhD in Intelligent Systems and Data Science (ISDS) is a thesis-based program that targets the need for highly qualified scientists to tackle challenges in artificial intelligence & machine learning, integrated smart systems, modern software systems, statistical/mathematical modelling & analytics, and big data infrastructure.  

The program is offered jointly by the Department of Computer Science and the Department of Mathematics and Statistics 

Graduates will proceed to research and/or teaching careers in academia, industry, government, and the community. 

Our Ph.D. in Intelligent Systems and Data Science is unique in many ways:

  • The degree title and focus areas are distinct throughout Ontario and Canada.
  • This interdisciplinary degree directly acknowledges the fundamental and intrinsic relationship between computer science, mathematics, and statistics.
  • The degree strives to foster a cohesive interdisciplinary program and community of students.
  • The qualifying examination requires students to write a research grant application. This experience will give students unique training in grant preparation.
  • The program allows students to gain experience in developing and applying advanced AI algorithms, complex software systems, data analytics tools, and statistical models.

For more information on Faculty Research, please visit the following pages:
Computer Science Faculty Research
Mathematics and Statistics Faculty Research

Entry point:

  • September


  • Thesis – 12 terms (4 years)

Application deadline:

January 15

Admission requirements

  1. Check the university requirements and the program requirements.
  2. Complete the online application and submit the non-refundable application fee.
  3. You will need to submit your transcripts as well as the following program specific materials:
    • Three academic references
    • Completed Statement of Research Interest that indicates potential supervisors
    • CV
    • GRE Scores (general or math test) optional

Career outcomes

Research and Teaching careers where they can tackle challenges in artificial intelligence and machine learning, mathematical modeling and analytics, and big data infrastructures:

  • Academia
  • Education
  • Government
  • Community

Research and Development Careers in Business and Industry where logical thinking, problem solving, and knowledge of qualitative methods are required:

  • Software Development
  • Information Technology
  • Startup companies
  • Business Intelligence
  • Insurances, Finances and Marketing
  • Medical and technological fields