The Lunenfeld-Tanenbaum Research Institute (LTRI) of Sinai Health, a University of Toronto-affiliated research centre, is seeking two (2) emerging leaders in the broad area of Population Health Data Science. The appointments will be for Full-Time Principal Investigators, rank equivalent to Assistant or Associate Professors, with the anticipated starting date of September 1, 2026, or a date to be mutually agreed upon.

We seek applicants who will develop independent, outstanding and innovative Population Health Data Science research programs. We will consider applicants spanning all areas of Population Health Data Science, including complex disease epidemiology, infectious disease research, risk prediction modeling, population and medical data linkage, geospatial data mining, multi-omics data integration, and artificial intelligence (AI) applications in health sciences, such as causal machine learning, deep learning for medical imaging, generative AI and more. The positions are open to both those who are specialized in methodological development, as well as those focused on innovative applications to impactful population health issues. The health topics include but are not limited to perinatal and maternal-child health, cancers, cardiometabolic conditions, autoimmune diseases and other complex health issues.

The Lunenfeld-Tanenbaum Research Institute is one of Canada’s leading biomedical research institutes, located within Mount Sinai Hospital at Sinai Health in downtown Toronto. The LTRI is dedicated to excellence in health research and the development of early-career investigators. LTRI’s faculty members are internationally renowned for their work in cancer, maternal-infant health, diabetes, inflammatory conditions, and genetic disorders among others. Large-scale health data has been collected through multiple research initiatives and platforms. Within the LTRI, the Prosserman Centre for Population Health Research comprises multi-disciplinary scientists focusing on quantitative research of complex diseases, including precision health and multi-omics data integration based on large-scale cohorts and biobank data. Partnering with the Data Sciences Institute, the Dalla Lana School of Public Health, the Department of Statistical Sciences, and the Department of Computer Science at the University of Toronto, the Prosserman Centre for Population Health Research is a hub for an active research community of public health research, complex disease epidemiology, omics data sciences and quantitative method innovation.

LTRI provides a research-intensive environment with modern and innovative core facilities. These include institutional high-performance computing clusters, biobanking as well as next-generation sequencing, single-cell platforms, proteomics, robotics, and advanced cellular imaging, which drive technology development and are housed in the Network Biology Collaborative Centre. LTRI has a fully accredited Biospecimen Repository for biobanking and a dedicated Research Trainee Centre that supports trainees across disciplines from around the world.

LTRI research groups engage in productive collaborations with the larger University of Toronto community, as well as national and international networks. The University of Toronto boasts one of the world's most concentrated biomedical research communities, and is notably home to the Toronto Academic Health Science Network (TAHSN), the Vector Institute for Artificial Intelligence and the Data Sciences Institute. Government agencies such as the Ontario Institute for Cancer Research and Public Health Ontario, with whom our researchers partner, are also based in Toronto. Toronto is a vibrant, safe, multicultural city with excellent quality of life.

2. Appointment Details
   Investigators at the Lunenfeld-Tanenbaum Research Institute are appointed to independent positions equivalent to Assistant, Associate or Full Professor, depending on experience. Preference for this open position will be given to individuals who qualify at the level of Assistant or Associate Professors. The Investigators will be cross-appointed at the University of Toronto in the academic department best aligned with the candidates’ backgrounds and research topics and, when applicable, with a possible affiliated appointment at the Vector Institute. The investigator will be integrated into the extensive network of data scientists affiliated with the Data Sciences Institute at the University of Toronto.

3. Education and Experience Requirements
   Candidates must hold a PhD, ScD, MD or equivalent doctoral degree, with postdoctoral or additional research experience and an established record of research accomplishment as demonstrated by outstanding publications, presentations at major international conferences, awards and accolades, as well as endorsement by reference letters. A track record of securing external funding and experience in cross-disciplinary collaborations is an asset. The successful candidates are expected to initiate and lead innovative, independent, and externally funded research programs of the highest international calibre and impact.

We offer competitive and generous salaries and start-up packages commensurate with experience and qualifications. As an equal opportunity employer who understands that diversity enriches our community and culture, we invite applications from all qualified candidates, including Indigenous Peoples, racialized people, disabled people/people with disabilities, women, and members of 2SLGBTQIA+ communities. The Lunenfeld-Tanenbaum Research Institute and Sinai Health recognize that scholars have diverse career paths and that career interruptions due to personal circumstances can be part of an exceptional academic record. Candidates are encouraged to explain any personal circumstances to allow for a fair application assessment. The committee will carefully consider any impact of career interruptions in its decision-making.

4. How to Apply
   Applications should include the following documents:
5. A cover letter
6. A one-page structured summary that includes: A) a brief education/training history; B) a summary of the applicant’s most important research contributions (up to five), and C) an abstract of the research plan
7. A complete curriculum vitae with complete publication list, and evidence of prior funding
8. A research statement highlighting the proposed research program (not exceeding 3 pages, including figures; references can be on a separate page)
9. A statement (0.5 to 1 page) highlighting past and future commitment to equity, diversity and inclusion (EDI). Please describe your strengths and experiences in promoting EDI in your previous institutional environments, as well as your commitment to supporting diverse trainees and colleagues in the future.
10. Three reference letters

Applications should be submitted via the Interfolio website prior to October 20, 2025: https://apply.interfolio.com/172529

Applicants needing additional information can contact the Search Committee Chair, Dr. Rayjean Hung via DataScience_search@lunenfeld.ca. Note that e-mailed applications will not be accepted.