Computer Science - Doctor of Philosophy (PhD)

Rear entrance of the Davis Centre building

The Davis Centre building (DC) on Waterloo's main campus

Pursue research and expand your learning with the PhD in Computer Science program.

You'll work with a supervisor to develop a thesis and conduct meaningful research that expands the scope of your graduate work. The program will prepare you to enter a career in academia, research or private industry.  

You'll also gain industry experience for in-demand careers with the option to apply to transfer to the PhD in Computer Science – Internship program after completing at least one academic term. 

The MMath in Computer Science is offered through the Cheriton School of Computer Science, which has been ranked number one nationally four years in a row based on program and research reputation according to the Maclean’s 2024 university rankings. Waterloo and the Cheriton School are among the top 25 universities internationally for computer science according to the 2023, 2022 and 2021 Quacquarelli Symonds worldwide university subject rankings, and attract exceptional students from all over the world.    

Program highlights

  • The Cheriton School of Computer Science has been ranked number one nationally four years in a row based on program and research reputation according to the Maclean’s 2024 university rankings. 

  • Learn from internationally acclaimed researchers.

  • Access research-intensive lab spaces.

  • Opportunities to publish your work and present at top conferences.

  • Own your work. Waterloo’s intellectual property (IP) policy means that everything you create is yours to keep. 

Research fields

  • Algorithms and Complexity
  • Artificial Intelligence
  • Bioinformatics
  • Computer Algebra and Symbolic Computation
  • Computer Graphics
  • Cryptography, Security and Privacy
  • Databases
  • Formal Methods
  • Health Informatics
  • Human-Computer Interaction
  • Information Retrieval
  • Machine Learning
  • Programming Languages
  • Quantum Computing
  • Scientific Computing
  • Software Engineering
  • Systems and Networking

Research project opportunities for this program

Exploring Artificial Intelligence (AI)/Machine Learning (ML) for Computational Models in Fintech

Financial technology, or Fintech, is a new trend that revolutionized the financial industry. Automated trading programs have become the new standard. Many of the financial activities that have been traditionally done based on human skills and experience have recently been replaced or will be replaced by computer systems. In fact, banks and investment companies are hiring more staff with strong computing skills than ever. Fintech is a broad subject and this research project is going to focus on quantitative analytics, and in particular on developing efficient and effective models for applications in finance.

Physical Simulation for Visual Computing

Our lab's research explores the intersection of computer graphics, computational physics, and geometry processing. We develop mathematical and algorithmic foundations for simulating complex physical phenomena, such as liquids, gases, and rigid or deformable materials, with efficiency, high fidelity, and robustness. By advancing computational methods for partial differential equations and dynamic surface evolution, we aim to make physically based animation both accurate and visually compelling.

We investigate a broad range of topics including multi-physics fluid-solid interactions, free-surface and multiphase flows, non-Newtonian and viscoelastic materials, and aspects of geometric representations, such as reconstruction of implicit surfaces (e.g., signed distance fields) and mesh-based topology tracking for dynamic surfaces. Our work bridges theory and practical application, often influencing research and production tools used in visual effects, animation, and interactive media. We strive to build well-grounded simulation methods that integrate physics, mathematics, and computation to push the boundaries of realism and control in the virtual worlds of the future.

Program overview

Department/School: David R. Cheriton School of Computer Science
Faculty: Faculty of Mathematics
Admit term(s): Fall (September - December), Winter (January - April), Spring (May - August)
Delivery mode: On-campus
Program type: Doctoral, Research
Length of program: 48 months (full-time)
Registration option(s): Full-time, Part-time
Study option(s): Thesis

Application deadlines

  • December 1 (for admission in September of the following year)
  • June 1 (for admission in January of the following year)
  • October 1 (for admission in May of the following year)

Key contacts

Computer Science Graduate Office

Computer Science Graduate Admissions

Shenghao Yang

There's a lot of opportunities, so it’s important to do what you like and just be open to the possibilities.

Shenghao Yang, Computer Science, PhD

Supervisors

  • Review the finding a supervisor resources.
  • It is not required to find a supervisor before applying. However, students are advised to establish contact with potential supervisors before applying.

Admission requirements

  • A master's degree in computer science with a 78% average.
  • Student with an undergraduate degree in computer science may apply for admission directly to the PhD program. Successful applicants will have an outstanding academic record, breadth of knowledge in computer science, and strong letters of recommendation.
  • PhD applicants may be admitted into the Master of Mathematics (MMath) program. Like all MMath students, they will have the option to transfer into the PhD program before completing the master's thesis if their performance warrants.

Degree requirements

Application materials

  • Resume
  • Statement of interest
    • A statement of maximum 500 words explaining your interest in and fit for the program you’re applying to, uploaded as a supporting document in the online application. Review the writing your personal statement resources for helpful tips and tricks on completion.

  • Transcript(s)

  • References
    • Three references are required; at least two academic.
  • Proof of English language proficiency, if applicable
    • TOEFL 93 (writing 22, speaking 22), IELTS 6.5 (writing 6.0, speaking 6.5)

Tuition and fees