Let’s SOLVE it
About the program
Let’s SOLVE it, together
If you are an undergraduate student with dreams of pioneering the next game-changing community solution using AI and ML, we want to help you get there.
Jumpstart your career
Build connections with ML industry experts and gain valuable technical guidance and training to explore career or further studies in AI and ML.
Solve real problems
Help improve your local community by creating a viable ML solution that solves a clear community problem. You will get all the support and mentorship from our team to turn your ideas into a viable proof-of-concept.
Discover how to apply AI to turn your ideas into reality
Give this semester more meaning and purpose outside of the course curriculum. We believe students can take ideas and make them happen, using cutting-edge technology and resources we can provide.
Work with a diverse cross-functional team
Get access to a diverse group of industry experts who can help you develop your idea and your skill set.
“We want to support students from a diversity of backgrounds, and geographic locations. The Canadian AI ecosystem is growing – new and diverse perspectives, and sensitivity to concerns specific to local communities, are needed.”
Dr. Greg Mori
Senior Director, Research
“Our Let’s SOLVE it program is part of our wider efforts to encourage and support diverse talent across the AI ecosystems. This initiative provides curious minds and raw talent with the skills, experience and contacts they require to thrive.”
Dr. Eirene Seiradaki
Director, Research Partnerships
“It’s been amazing to be part of the LSI program as a mentor and help the participants take their innovative ideas to the next level. I’m proud to work at a company that invests in future AI scientists and practitioners.”
Sr. Machine Learning Software Engineer, LSI Mentor
How it works
We are looking for teams of 3 to 5 undergraduate students with ideas on how AI / ML could be used to tackle a specific community problem. Here’s how the program works:
This program is open to all undergraduate students at all Canadian universities.
The mentorship program is free and will be conducted virtually. With this program, we aim to support students from a diversity of backgrounds, geographic locations and universities.
You don’t need to be enrolled in a Computer Sciences program – if team members have some basic programming knowledge, this will help; but specific experience using AI or ML isn’t necessary.
The upcoming cycle will run for two months, from March through April 2023.
Frequently asked questions
Let’s SOLVE it is a mentorship program aimed at providing undergraduate students with the opportunity to gain industry exposure and networking experience by working closely with members of the Borealis AI team. During the two months of the program, your teams will work with Borealis AI mentors on projects using Artificial Intelligence and Machine Learning to tackle the challenges of your community. While working on your selected projects, you will also learn about career opportunities in the thriving AI industry.
Please gather the following materials in order to proceed with your application. You will not be able to save the application once you start. Select one of your team members to be the team captain.
For each team:
A proposal of 500-100 words. Each team can submit a secondary project; however, please note that the adjudication committee will judge your application based only on your primary project proposal. If your team is selected, both the proposals you submitted will become available to your mentor to choose the best fit for your team to work on during the program. Your outline should include the following:
Why that problem is important to your team and/or your community;
• Why your team believes Machine Learning could help solve this problem, and two to three potential datasets to use.
• If this project is related to a personal, extra-curricular project you have already been working on, or if it is part of coursework you have to do for one of your university classes.
For each team member:
• General information
• Educational background
• Skills/interests in computer science
• Proof of enrollment and year of study at a Canadian university for each team member (latest transcripts, letter of acceptance)
• Resume (optional)
This mentorship program is open to teams of 3 to 5 undergraduate students currently enrolled at a Canadian university or college.
All team members must meet the following additional criteria:
• Each team must have 3 to 5 students
• Each team member must be able to dedicate 10 hours each week to this project between • May 1 – July 1, 2022, including one 1-hour team meeting and one 30 min meeting with their Borealis AI mentor each week.
• An introductory undergraduate or high school programming course.
During the two-month remote mentorship program, you will have the opportunity to collaborate with Machine Learning Researchers and Engineers. During the term of the mentorship program, you can expect:
• Industry exposure. You will receive guidance from, and access to, a diverse group of industry experts at Borealis AI.
• Mentorship. A Borealis AI team member will work closely with your team to help you formulate your Machine Learning proposal and provide advice on future career opportunities.
• Contacts. You will be provided with the opportunity to network and build connections with industry experts in Machine Learning and programming, which can help you as you chart a path forward in your professional life.
• Training. In addition to direct technical guidance from your mentors, you will receive general guidance and training to help you progress through a curated selection of the best public resources for personal education in Machine Learning and programming.
The final outputs of the mentorship program will include:
• A presentation. A 15 minutes talk/slide presentation to the Borealis AI team, outlining the work undertaken and the proposed path forward.
• A one-page report. A written short summary of the final presentation.
• A public code repository. Storing any tests or proof of concepts from the project.
• A blog post. You will work with our team to write a short blog about your LSi program experience and project outcomes.
• A white paper. An expanded, formal treatment of the original proposal with a precise plan for how Machine Learning can be used to help with the problem outlined and what work is required to make the solution a reality. (Optional)
ML knowledge is not required to apply but you do need to be interested in learning about ML.
Only team applications are eligible. Teams can be made up of students from different programs and at different Canadian universities. So, think broadly about how you build your team.
Only team of 3 to 5 members are eligible for this program.
While all of your team members must be enrolled in a Canadian university or college for the Spring semester of 2023, they don’t necessarily have to be studying at the same university.
You can still submit your team application and mention this in the “Additional comments” section. Please keep in mind, however, that if you are selected for the program, your team must have availability in common for at least 2 hours from Monday-Friday 9.00am to 5.00pm in EST time zone for the duration of the mentorship program. In addition, all team members must be available for the Welcome Day Event and Presentation Days at the end of the program.
The program is entirely virtual. As long as you are enrolled in a Canadian university and you are able to attend the weekly team meetings with your mentor, the Welcome Day Event and the Presentation Days, you are eligible to apply.
You can still submit your application, but please give us as much information as possible about how you intend to use the project in the applicable section of your team application. Your application will be reviewed separately, taking into consideration the explanation you provided.
You can apply with a maximum of 2 different teams. And, if both are selected to attend Borealis AI’s mentorship program, you will be asked to decide which team you want to be part of. However, if one of the two teams do not meet the requirement for the minimum or maximum number of team members (3-5), then the decision will be made by the Borealis AI selection committee.
Yes, you can apply to this program. As long as you are enrolled in a Canadian university or college for the Spring semester of 2023, you are eligible.
To avoid multiple email exchanges, we ask that one of your team members becomes the main point of contact for the whole team. The rest of the team members should be cc’ed on all communications. However, we ask that only the team captain replies to our e-mails to confirm interviews and other team matters.
If your team moves to the second part of the selection process, Borealis AI will reach out to your team’s point of contact to schedule an informal chat between your team and a Borealis AI team member. During this informal chat, you can provide more details about your proposed project and the technical experience of your individual team members. Here are some example questions to think about:
• Why did you choose this topic?
• Do you know what data you can use for your project?
• How do you describe your programming skills?
• Do you have experience with ML?
• What do you expect of the Let’s SOLVE it Program?
These questions are for the team captain; you will need to enter this person’s contact information there.
All teams that submit an application will be notified on February 20th, 2023. If you are not selected this time around, you are welcome to apply again in any of the following cycles of the mentorship program.
Presentation Day is the end of the program. All teams will present the project they have been working on during the mentorship program. All teams need to attend this event.
Welcome Day is the first day of the program. During this 2-hour virtual meeting, we will introduce all participant teams, their affiliated university, project and mentor. We will also share important information such as how to get in touch with your mentor, what workshops we scheduled during the program and what outcomes you can expect.