The Cheriton School of Computer Science is looking for exceptional students currently enrolled in a Computer Science program or related areas who have a keen interest in research and in pursuing graduate studies. This award is open to students at any university.  

Students will participate in a four-month, full time, research term to work directly with a faculty supervisor in a particular research area (e.g., Computer Security, AI, Human-Computer Interaction, Theoretical Computer Science, etc.).

  • Learn the research methodology related to a particular field of interest (see projects below)
  • Review existing literature and develop new research questions.
  • Work with a supervisor and a team of graduate students to address the research questions, which may involve developing systems, creating algorithms, solving mathematical problems, designing experiments, etc.
  • Work on publications to disseminate research findings to relevant academic conferences.

Meet Dmitry

Dmitry is a URF award recipient and spent the Fall 2020 term under the supervision of Professor Joanne Atlee and Michael Godfrey on the Rex project. The key in Rex lies in minimizing the information extracted from source code, thereby allowing for the analysis of very large systems. The analyses themselves involve discovering paths within the “fact based” graph extracted by Rex. Dmitry’s role revolved around improving the accuracy of these analyses by incorporating control-flow information into the extracted facts. Dmitry shares the highlight of his experience working on the Rex project and how it compared to past co-op positions.


“I think my favourite part about the internship was the amount I learned. Reflecting back to my previous co-ops, I think this was probably the most independence and ownership I was ever given on any project. As a result, I had to very quickly and very thoroughly learn my problem’s domain such that I could make progress. I learned a lot about the compiler tools involved in static analysis, such as ASTs and CFGs, and I came to realize that I really enjoy static analysis work. Apart from interesting technical knowledge, I also learned a great deal about abstract problem solving, since that was a huge component of my daily routine. I learned that open-ended problem solving is something that I find very fulfilling, and the new skills that I gained from it will definitely help me in future work.” Dmitry Koberts

View past URF award winners

Application Deadline

URF Term Application Deadline
Fall 2023 Monday, May 15, 2023 (9:00 am)
Winter 2024 TBD (mid September)
Spring 2024 TBD (mid January)


URF recipients will receive a minimum of $12,000/term:

  • $7,500 contributed by the Cheriton School of Computer Science
  • Remaining provided by faculty supervisor (and/or NSERC USRA, Faculty of Mathematics MURA)


  • Students who are currently in 3rd or 4th year are eligible to apply; exceptional students from earlier terms will also be considered.
  • A cumulative average of at least 80% is required.
  • Preference is given to students enrolled in the Computer Science major or related programs (i.e. any program that would prepare a student for Computer Science graduate studies). 
  • The faculty supervisor must have an appointment or cross-appointment in the School of Computer Science

A student can only do one URF per term, and must be either on a co-op term or not taking courses. Note that International Students need a SIN# and work permit to work in Canada. URF recipients normally work on campus at the University of Waterloo, but due to pandemic restrictions, some or all positions may be remote. If remote, it is expected that students will be working from a location within Canada.

Open and Sponsored Applications 

There are two types of URF applications: 

  • A sponsored application means you and a faculty member already have a connection, you've already discussed a specific project to work on, and they're providing a reference letter that states that they'll hire you as a research assistant if you're awarded a URF.   

  • An open application means you want to be matched with a faculty supervisor. Potential supervisors list projects or research areas near the bottom of this page, and you will indicate your interest in specific projects in your application. 

How to apply

The application has two parts: an online information form and supporting materials submitted to a secure file server.  

Information Form 

The information form gathers basic information and provides some additional checks that your application is submitted correctly. It should be completed when you’re ready to submit the single PDF with your cover letter, resume, and transcript (see next part).   

[ Information Form

Supporting Materials  

1. A single PDF containing a cover letter, resume, and transcript. Your PDF file must have the filename “YourFirstName_YourLastName.pdf” and it must contain these items in the following order: 

  • Your cover letter should be 1 to 2 pages with: your research interests; why you want to pursue a URF; what your future plans are for graduate school; why you're interested in working on the specific project(s) you selected or the project you're already sponsored for. 

  • Your resume should be up-to-date and highlight relevant skills and experience. 

  • Your transcript(s) should be current and list all of your undergraduate courses and grades. 

2. A letter of recommendation from a professor (or equivalent person with authority).  Each letter must be a PDF file with the filename “YourFirstName_YourLastName_ReferenceLastName.pdf”.  

  • For open applications, a letter of recommendation from a professor is optional (but encouraged). 

  • For sponsored applications, a letter of recommendation from the sponsoring faculty member is required.     

All supporting materials must be submitted to this secure file server: ] 

Please note that incomplete applications (i.e., missing any of the required items above) will not be considered.

Open Projects and Faculty for Fall 2023

Faculty with Specific Projects 

  • Operating system kernels - theory vs practice (Martin Karsten) Operating system kernels are fairly big and very complicated software entities that address complex resource management challenges and typically support a massive set of hardware devices. Meaningful research into the structure and performance of operating systems is hampered by a significant barrier to entry: a research operating system must support a reasonable set of modern hardware devices to obtain useful performance measurements beyond simplistic benchmark tests. The overall goal of this project is lowering that barrier to entry by building a simple kernel nucleus and combining it with 3rd-party-open-source software to support a large variety of device drivers. The critical next step is hollowing out an existing open-source operating system kernel and making the hardware support components independent of the core generic resource management services. This will result in a novel open-source research platform that enables subsequent studies on structural and algorithmic innovations for operating system kernels. [karsten-f23]
  • Physics simulation for computer graphics (Chrisopther Batty) Emphasizing numerical techniques for liquids and gases along with their interactions with other natural phenomena. [batty-f23]
  • Advanced Hockey Analytics (Tim Brecht) Recently, the National Hockey League (NHL) deployed a player and puck tracking (PPT) system that records the location of every player and the pick with high resolution and frequency (12 and 60 time per-second for players and the puck). Traditional methods of performance evaluation in hockey have replied mostly on offensive events like goals and shots despite these representing only a small fraction of the action game play. The goal of this research is to devise, compute and evaluate interesting and valuable new metrics that can be used by fans, hockey broadcasts, reporters and sports pool and betting sites to increase fan engagement by players coaches, agents and executives to provide new and deeper insights into player and team performance. A key component of this research will be to develop analytics and techniques for computing metrics in real time. Thus enabling augmented reality experiences that could overlay statistics on video feeds and/or depict real-time animated visualizations showing and providing for live, in-game analysis. [brecht-f23]

Faculty with General Research Areas

Jian Zhao: I work in the fields of Human-Computer Interaction and Information Visualization on topics such as advanced visualizations for explainable AI, intelligent interfaces for creativity support, intractive tools for data science, and visual analytics in augmented/virtual reality. [zhao-f23]