The MARC-Osler Initiative is a research group that combines clinical medicine with computer engineering. We build computational systems that model how diseases work. We build discovery engines: integrated infrastructures that distill multi-omic and physiological complexity into translational models. By focusing on finding the actual causes of disease rather than just identifying patterns, we help researchers understand the brain at a molecular level.
Engineering Computational Platforms to Unmask the Logic of Brain Disease
Our Core Scientific Principles
We help researchers move beyond writing literature reviews. We teach them how to build computer models to study disease.
We use large public databases to study the genetics and chemistry of how the brain ages and breaks down.
We create and share free software (including AI and Machine Learning) so other scientists can study brain tumors and strokes more effectively.
How We Operate
Our programs focus on teaching accessible, reproducible forms of medical research that students and clinicians can conduct regardless of institutional resources:
1. Research Education Programs
We teach practical methodologies that allow students and clinicians to conduct meaningful research using accessible resources. Core training areas include: • Systematic Reviews and Meta-Analyses (SR/MA) • Evidence synthesis and literature analysis • Computational biomedical research • AI-assisted research workflows • Research methodology and scientific writing Our goal is to help participants move from reading research to producing it.
2. Mentorship and Research Collaborations
Participants are paired with experienced mentors who guide them through the research process, from forming a research question to preparing a manuscript for publication. Mentorship focuses on: • Developing clinically meaningful research questions • Designing reproducible research workflows • Navigating academic publishing • Building long-term research careers
3. Open Computational Research
Modern biomedical discovery increasingly relies on computational approaches. We help trainees conduct research using publicly available datasets and open-science tools. Examples include: • Clinical datasets • Genomics and transcriptomics databases • Medical imaging repositories • Public health and epidemiology datasets Participants learn how to use modern computational tools—including AI—to explore real scientific questions and generate publishable insights.
4. Research Access Sponsorship
Many talented researchers lack the financial resources required to complete and publish research. Through donations and partnerships, the Osler Prize supports: • Publication fees for open-access journals • Cloud computing credits for data analysis • Research software access • Educational scholarships Our goal is to remove structural barriers that prevent talented individuals from contributing to science.
The Osler Prize Initiative
The Osler Prize highlights outstanding research contributions from students and early-career clinicians participating in our programs. Projects span multiple domains of medical research, including: Clinical medicine, Public health, Biomedical data science, and Evidence-based medicine
Partners from
