Presented by

AI in Finance Summer School

A research training program

The frontier of AI
in finance.

An AI in finance summer school for PhD students in machine learning and AI.

Explore cutting-edge AI research that powers important financial applications through talks, tutorials, research discussions, hands-on challenges, and direct access to leading researchers and industry scientists.

Discover a domain that presents some of the most demanding testbeds for core ML and AI problems, where your research can have real impact.

Open application form View program

Dates

Aug 24–272026

Location

Vancouver, BCIn-person

Eligibility

PhD studentsCanadian universities

Program

About the program.

You'll have the opportunity to learn, connect, and tackle real-world challenges shaping the future of AI in finance.

Keynotes & talks

Sessions from leading researchers in machine learning, quantitative finance, and AI safety — surveying the open problems shaping the next decade of the field.

Hands-on tutorials

Participate in interactive sessions led by researchers and practitioners. Topics may include foundation models, generative AI, reinforcement learning, causal inference, time-series foundations, and other applied machine learning methods.

Student poster sessions

Curated poster sessions are designed to spark discussion, feedback, and future collaboration.

Participant challenges

Work in teams on open-ended AI challenges inspired by real-world problems. Apply research thinking, experiment with approaches, and present your findings at the end of the program.

Panel discussions

Cross-disciplinary panels on topics including responsible AI in financial systems, model risk, the academic-to-industry transition, research-to-production challenges, opportunities at the frontier of machine learning in finance, and more.

Networking

Curated dinners, lab visits, and small-group office hours with faculty and industry scientists. Designed to outlast the week.

Community building

Join a growing network of researchers across Canadian universities and industry. The connections made here are designed to extend well beyond the summer school.

RBC Borealis is the Royal Bank of Canada's AI research and innovation division and a leading contributor to Canada's artificial intelligence ecosystem. Founded in 2016, RBC Borealis brings together researchers, scientists, engineers and data experts to advance AI through world-class research, industry collaboration, and real-world applications in financial services.

As part of RBC's AI Group, RBC Borealis transforms cutting-edge research into enterprise-scale innovation and impact. Through collaborations with leading academic institutions, partnerships across the AI community, and the development of advanced AI solutions, RBC Borealis is helping shape the future of AI in financial services while fostering the next generation of AI talent.

Dates & location

West Coast, Canada. This summer.

When

August 24–27

Four days designed to immerse participants in the intersection of AI in financial services.

MON—THU20264 DAYS50 STUDENTS

Where

Vancouver, BC

Hosted in Vancouver. Additional venue, travel, and accommodation details will be provided to admitted participants on offer.

RESEARCH HUBCOMMUNITYCANADA

Eligibility

Built for AI researchers.

Enrolled at a Canadian university.Currently studying at a degree-granting institution in Canada at the time of application.

Pursuing a PhD.Doctoral candidates in any year of study. Visiting and exchange PhDs at Canadian institutions are eligible.

Quantitative discipline.Computer science or a related field — mathematics, statistics, physics, economics, engineering, or a comparable program.

Proficient in Python.Comfortable building and experimenting with modern machine learning tools and Python.

Demonstrated interest in AI. Finance experience is not expected.Evidence of research, projects, publications, open-source contributions, or other meaningful engagement with AI and machine learning. Participants come from a wide range of AI research backgrounds, including computer vision, NLP, RL, AI systems, statistics, and machine learning. The program is designed to introduce researchers to the opportunities and challenges of applying AI within financial services.

CV or resume.A current academic CV detailing education, research, publications, and relevant projects.

A capable laptop.Able to run modern AI/ML tools and software locally during tutorials and challenges.

Faculty & speakers

The 2026 roster: coming soon.

Hear from leading researchers across academia and industry. The 2026 speaker lineup will be announced soon.

More details

Frequently asked questions.

01Is there a fee to attend?

Upon acceptance, there is a registration fee: $550 CAD (no accommodation provided) or $1,500 CAD (4 nights' accommodation provided). Fees cover lunch, refreshments, social events, and access to all curriculum. Flights are not included.

We are committed to making this program accessible to qualified students regardless of financial constraints. Bursary applications will be accepted alongside program applications. Details on eligibility criteria and award details will be announced soon.

02I'm a Master's student — can I apply?

The 2026 cohort is reserved for PhD students at Canadian universities. We expect to open additional formats to Master's researchers in future years.

03Do I need a finance background?

No. The program is intended for researchers with backgrounds in machine learning and AI. Financial services is the application domain explored throughout the week, and no prior knowledge of banking, finance, economics, or financial markets is required. We expect participants to bring AI expertise and curiosity; we provide the domain context.

04What does a typical day look like?

Days typically include research talks, tutorials, collaborative challenges, poster sessions, and networking opportunities and activities.

05How are applications evaluated?

Applications are reviewed holistically based on research interests, technical background, demonstrated engagement in AI, and overall fit with the program.