Twenty-one McGill research projects were funded by the New Frontiers in Research Fund 2019 Exploration Grants to explore, take risks, and lead non-traditional research.
The New Frontiers in Research Fund (NFRF) 2019 Exploration competition awarded $46.3 million in funding to support 186 research projects that bring disciplines together in non-traditional ways to explore new research directions. McGill researchers will receive $5.2 million shared among 21 projects, with each receiving up to $250,000 over the next two years.
The NFRF’s Exploration stream addresses gaps in the federal funding system to promote innovation. It supports research that defies current paradigms, bridges disciplines, or tackles fundamental problems from new perspectives. A key principle of this stream is the recognition that exploring new directions in research involves some risk, but is ultimately worthwhile given the potential for significant impact.
McGill’s funded Exploration projects support a wide range of topics—from resolving microbial carbon transformations in a warming world, to using machine learning to build a comprehensive database of disclosure information, to reverse engineering the neural circuits of perception.
The NFRF is an initiative of the Canada Research Coordinating Committee and is managed as a tri-agency program on behalf of the Canadian Institutes of Health Research, the Natural Sciences and Engineering Research Council and the Social Sciences and Humanities Research Council.
Faculty of Medicine-affiliated 2019 NFRF Exploration competition recipients, and their projects, are:
- Sara Ahmed: Holistic evaluation of the determinants of mobility to enhance social and work participation: Platform trial of the Electronic Mobility Monitoring and Intervention (EMMI) Portal
- Julia Burnier: Microfluidic Systems for nanoparticle synthesis and characterization to understand cancer cell-derived EV uptake
- Amin Emad: A machine learning framework for preclinical-to-clinical drug response prediction and identification of therapeutic targets
- David Juncker: Rapid identification of antibody-producing cells against viral agents of new emerging threats and epidemics
- Nicholas King: Automating Scientific Transparency: Using Machine Learning to Build a Comprehensive Database of Disclosure Information
- Arjun Krishnaswamy: Reverse engineering the neural circuits of perception
- Hamed Shateri Najafabadi: Understanding the driving forces behind cellular heterogeneity in cancer
- Stuart Trenholm: A closed-loop brain stimulation system for vision restoration following damage to visual cortex
- Stephanie Weber: Organization and function of the dinoflagellate genome
July 22 2020