Applications now open for DSI-T-CAIREM Catalyst Grant for Data Science in Medicine and Health (LOI Deadline: July 10)
Applications now open for DSI-T-CAIREM Catalyst Grant for Data Science in Medicine and Health
This co-sponsored grant is a competitive seed funding program for multidisciplinary teams focused on the development of novel statistical or computational tools and the use of existing methodology in innovative ways.
Co-Sponsored Stream DSI-T-CAIREM Catalyst Grant for Data Science in Medicine and Health
Letter of Intent Deadline: July 10
Full Application Deadline: October 30
DSI-T-CAIREM Catalyst Grant for Data Science in Medicine and Health
The DSI is pleased to partner with The Temerty Centre for Artificial Intelligence Research and Education in Medicine (T-CAIREM) to co-fund Catalyst Grants focused on research in artificial intelligence across the medical and health sciences that translates into real-world clinical settings. CRTs can indicate that they are applying for the DSI-T-CAIREM Catalyst Grant for Data Science in Medicine and Health on the application form’s Administrative Information tab.
Please note that the eligibility requirements for the DSI-T-CAIREM Catalyst Grant for Data Science in Medicine and Health are expanded for CRTs to include T-CAIREM scientists and researchers who are not currently at DSI partner institutions as Co-PIs. NPIs on these applications must be eligible to hold DSI funding as outlined in the Eligibility section below. All team members must be T-CAIREM members.
Pillars
The DSI has surveyed our competitors to date and identified four pillars of strength in which our research community is dramatically advancing new methodologies. To further build capacity and new collaborations in these areas, we are asking that applicants to our larger competitions categorize their proposed projects within these pillars:
1. Predictive Analytics & AI
Projects developing advanced methodologies and AI to predict features or occurrences.
2. Heterogeneous Data: Tools & Feature Engineering
Projects advancing methodology that allows for combining structured and unstructured data from different sources or for developing new features for data categorization.
3. Translation: Visualization, Data Communication, & Policy
Projects translating data through innovative visualization or other novel methods of communication into actionable insights.
4. Causal Discovery & Analysis
Projects developing causal or other advanced methods of analysis for discovery within existing datasets.
Applicants are free to select more than one pillar; however, they will be expected to substantively demonstrate how their work aligns with the overall competition call for each pillar selected. For example, if a project that clearly aligns with the call by advancing novel or innovative predictive analytics methodologies (pillar 1) also includes a common visualization method for knowledge transfer that, on its own, would not align with the competition call, the candidate should only select pillar 1 and not pillar 3. Reviewers will be instructed to assess and score each proposal based on its alignment to the overall competition call within the framework of each indicated pillar.