The Data Science Institute invites applications from PIs within the Faculty of Science for the Data Science Catalyst Program. This 2-year pilot initiative aims to support Faculty of Science PIs in enhancing the data science aspect of their research endeavors, thereby increasing their potential for securing future research grant funding.
Through the Data Science Catalyst Program, funded projects will be paired with a DSI resident data scientist for a duration of one year, focusing on data-intensive projects. PIs are only required to submit a grant proposal incorporating some of the outcomes achieved with the assistance of the DSI resident data scientist at the end of the one-year period.
Starting 2024, two DSI resident data scientists will collaborate on a total of four projects with PIs from the Faculty of Science each year. The DSI will issue an open call for project proposals twice a year. The first call closed in May 2024 and the brief description of selected projects in Round 1 can be viewed at the bottom of this page.
Updated December 15, 2024: Round 2 of the call for proposals is now closed. Please stay tuned for the next call!
Multiple PIs from different faculties can submit a single project proposal, provided that the team includes at least one PI from the Faculty of Science.
Priority considerations will be given to projects if the data collection has already been completed and/or if the PI can identify at least one trainee with adequate computational skills in their team to collaborate closely with the DSI resident data scientist. In addition, EDI will also be considered.
All applications will be evaluated by an adjudication committee comprised of members of the DSI Executive Committee.
An online information session was held on Thursday, May 2, 2024. The recording and key points of discussion are posted below.
Information Session Recording & Summary of Discussions
Key points of the discussion from the Information Session
Project Proposals:
- Applicants are encouraged to submit their project proposals even if they’re uncertain about the level of interest from a data science standpoint. Feedback provided by the Adjudication Committee will assist them in refining their proposals for subsequent rounds in the event of unsuccessful outcome in the first round.
- Typically, proposed projects will likely fall into one of three categories: (1) issues unrelated to data science, but more aligned with software or other disciplines; (2) relatively straightforward problems suitable for a resolution with the assistance of a co-op student; (3) complex data science challenges that align with the DSI’s objectives.
- No specific preference will be given to multiple-PI projects over those with a single PI. The final ranking will be determined by the Adjudication Committee.
- Because of time limitations, the Adjudication Committee cannot offer feedback to PIs before project proposals are submitted. Please submit your project proposal and feedback will be provided.
Support from DSI:
- DSI resident data scientists possess postgraduate qualifications with extensive professional data science experience spanning many years. They are not recent graduates with limited experience.
- DSI Director, Dr. Raymond Ng, will supervise the projects, offering guidance and mentorship throughout the one-year duration of the Program.
IP & External Grant Applications:
- No formal agreement exists regarding the IP potentially arising from the Program. All IP rights are vested in the PI and their team, not the DSI, with no claims to IP by the DSI. There may be exceptions, but unlikely.
- PIs are not obligated to engage the DSI in their future external grant applications. While involvement is possible and subject to mutual agreement, there is no expectation for it.
PI’s Trainee:
- Preference would be given to graduate student trainees over undergraduate student trainees, primarily because graduate students typically have greater availability to dedicate to the project for an extended duration compared to undergraduate students.
- DSI will not offer additional financial support for the trainees in the PI’s lab.
