For students: Research Practice Guidelines

All new students joining the lab are encouraged to read this document, outlining our working practice: Research Practice Guidelines (PDF).

Our lab explores questions such as:
– How do people form new theories and explore in the real world?
– How do people reason effectively in complex in long-horizon tasks?
– How can humans and machines work together to invent new concepts and tools?

Working in our lab

The Bayesian said he'd probably be at the party, but he'd update me.
(If you laughed, you will fit in.)

Our lab connects a collaborative group of researchers at various career stages, with many active international collaborations. Because conference participation is important, the lab guaranteed funding to travel to major AI and cognitive science conferences for active contributors.

Advisor funding is available to lab members, but the Canadian funding structure is not designed for a single funding source as a living income. Graduate students are encouraged to actively seek scholarships, fellowships, and stack multiple funding sources — funding acquisition is a technical skill that all graduate students should develop.

We accept expressions of interest from self-motivated prospective PhD students and strong undergraduates interested to build research experience. Applications for directed study and honours projects are welcome.
We do not offer funding to international MSc students (ocasional support is available for exceptional Canadian applicants).
MSc is not required for prospective PhD applicants with prior research experience.

Lab member responsibilities

• Develop, and implement computational models
• Prepare slides and progress reports for weekly meetings with academic advisors
• Work effectively with the group toward conference deadlines (i.e. NeurIPS, ICLR, Cognitive Science Society)
• Assist with, and eventually lead, journal publications (PLOS, Cognition, Nature group journals)
• Analyze data, fit statistical models, and generate plots
• Design behavioral experiments and write scripts to process behavioral data
• Present research as posters and talks, informally to collaborators and at conferences
• Contribute to teaching at bachelor's level as a teaching assistant
• Proactively apply for scholarships and seek funding opportunities

Skills we consider in evaluating prospective PhD applicants

• Strong mathematical foundations — ability or willingness to formulate and prove theorems and analyze algorithms theoretically. Strong psychology or neuroscience graduates without a solid math background, but a willingness to learn foundations, are welcome to apply.
• Research experience in a quantitative discipline: cognitive psychology, mathematics, physics, computer science, neuroscience or related fields.
• A record of publications at international venues.
• A working knowledge of coding (e.g. we use Python), statistics, and AI/ML.
• Excellent written and spoken English.
• Self-motivated, organized, and proactive.
• Familiarity with LLM API, scientific computing libraries, and coding agents.

Join Us!

Contact us to express interest.

Please include in your email:

• Which research question(s) you want to work on
• Which papers, books, or blog posts inspire your thinking
• Your background in mathematics, psychology, and prior research experience
• Your CV

We do not respond to AI-generated emails, generic inquiries, or emails that do not address the above.

The easiest way to join as a PhD student is to have worked with us previously, by contributing to one of our projects. The easiest way to join as an undergraduate is to send your CV, transcript, and a brief email outlining your background and prior research experience.