Interested in the LEAF lab?

We are regularly looking for exceptionally creative, talented, and self-motivated researchers, from undergraduates to postdocs. Our research typically requires strong programming, mathematics, and machine learning foundations. If you think this describes you and you are interested in working together, please read this page carefully before reaching out.

Graduate Programs (Ph.D. & Master’s)

These are research-intensive programs with a small amount of coursework. You will develop collaboration and communication skills within the LEAF lab, the Robotics Institute, and UTIAS or DCS. Applicants from all academic backgrounds are encouraged to apply.

The Ph.D. program will train you to be a successful and independent scientist in 1+ of our fields of research. The Master’s program serves as a stepping-stone to prepare you for Ph.D.-level research.

I am generally open to co-advising with other faculty in UTIAS and DCS. If your interests span two groups, name your preferred co-advisor(s) in your application.

How to apply

Step 1: Apply through one of the routes below. Mention the PI’s name in your application, and describe your research interests with reference to specific papers or directions from our publications, not just a general interest in robotics or ML. Applications without the PI’s name, or that show no specific engagement with our research, may be overlooked.

Step 2: Interview. Shortlisted candidates will be invited for a virtual interview to discuss background, goals, and potential research directions.

Routes to joining

Funding

Many competitive applicants either hold or are actively applying for external funding. If you’re a Canadian citizen or permanent resident, apply for an NSERC CGS-M (Master’s) or PGS-D (Ph.D.) award; Ontario residents should also apply for an OGS. If admitted, ask about Vector Institute scholarships. Mentioning that you’ve applied, or plan to, is a meaningful positive signal: the strongest applications typically do.

Coursework

UTIAS Ph.D. and M.A.Sc. programs require 4 courses total, of which 2 must be classified as Robotics (ROB) or Aerospace (AER). The remainder can be chosen in coordination with your advisor. See the Robotics course list and program-specific requirements. For CS programs, see their program descriptions.

Visiting Researchers

I welcome experienced researchers to consider a research visit and occasionally would host them. I only host experienced researchers with established track records, ideally evidenced through publications at the primary venues we publish at (see Contact), with rare exceptions. If you think you’re a good fit, please see the contact guidance below.

Undergraduate Researchers

We sometimes involve undergraduates in our research, and welcome you to consider it. For these involvements to be meaningful, we’re looking for a minimum of 10 hours/week of effort sustained for at least one semester. Please don’t reach out unless you can realistically commit to that. Good research requires time and persistence. Prior research experience isn’t required. We typically expect you to be strong in at least two of the following: programming, mathematics, and machine learning.

Contact

Email: nick.rhinehart@utoronto.ca

If you’ve carefully read this page and want to reach out, please include [LEAF-interest] in your subject line. Emails that follow this format are likelier to get replies:

• One or two specific things from our recent publications that connect to your background or interests.
• A concrete question or idea, however small, rather than an open-ended request to discuss opportunities.
• Links to 2-3 of your representative papers, ideally published or under review at our primary venues (e.g., NeurIPS, ICML, ICLR, CVPR, ICCV, RSS, CoRL, ICRA) and related to our research areas.
• Your CV, which route (see above) you’re asking about, and your funding situation if applicable.
• Written by you: I often ignore application emails written by LLMs for a variety of reasons.

No response does not necessarily mean we are not interested. If you don’t receive a response, yet have carefully read this page and strongly believe you are an excellent fit to do research with us, please try to contact us again.

FAQ