Company Bio

North York General is one of Canada’s leading community academic hospitals with a vision to deliver World-Class Care, 24/7. Affiliated with the University of Toronto, our multi-site campus supports our diverse community through every stage and life-defining moment by providing a wide range of acute care, ambulatory and long-term care services.

What defines North York General goes beyond exceptional quality care. Our superpower is how we deliver that care – the unparalleled compassion we bring to every encounter, during the moments that matter. Through partnerships, collaboration and academic endeavours, we seek to set new standards for People-Centred Care—a cornerstone of our culture and central to our Mission: People-Centred Care for a healthier community.

North York General is a member of the North York Toronto Health Partners, an Ontario Health Team that integrates local care with patients, primary care and community partners.

We are proud to be a place where the best people come to learn, grow and innovate.

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Position Summary

Post-Doctoral Fellow, Occupational Health Data and Health System Research North York General Hospital is seeking a Post-Doctoral Fellow to work under the supervision of Dr.

Karen

Tu, Occupational Health Data Lead, on a program of occupational health, health services, and health system research focused on improving outcomes for workers recovering from workplace injuries and illnesses. The successful candidate will take a leadership role in developing and implementing a series of research projects aimed at improving the effectiveness, quality, equity, and integration of healthcare services across occupational health and broader health system settings. Research activities will involve literature reviews, advanced quantitative analyses, database development, and collaboration with clinicians, healthcare organizations, policy-makers, and researchers. Occupational Health Data Platform Development A major focus of this fellowship is the development of a novel occupational health data platform to support research on workplace injury, rehabilitation, and return-to-work outcomes.

The successful candidate will lead the creation and validation of a longitudinal research database based on electronic medical record (EMR) data. This initiative will involve extracting, harmonizing, and linking occupational health data with radiology and diagnostic imaging reports, emergency department records, hospital admissions, physician services, and primary care EMR data to create a rich research resource for evaluating care pathways, healthcare utilization, disability trajectories, mental health outcomes, and recovery following occupational injury. The database will serve as a foundation for future research, predictive modeling, quality improvement initiatives, and policy-relevant studies aimed at improving care and outcomes for injured workers.

In addition to leading database development, the fellow will contribute to a growing occupational health research program focused on workers recovering from workplace injuries and illnesses. Research projects will use the database to evaluate care pathways, timeliness of care, return-to-work outcomes, loss-of-earnings trajectories, mental health service utilization, and predictors of recovery following occupational injury. Projects will involve advanced epidemiologic, health services, and predictive modeling approaches,



including machine learning and longitudinal analyses.

Potential research projects may include:

- Mapping care pathways across occupational injury types and evaluating patterns of healthcare utilization.
- Evaluating delays in care and adherence to WSIB service-level agreements and performance targets.
- Identifying predictors of successful and delayed return-to-work outcomes.
- Developing prediction models for loss-of-earnings and prolonged disability following workplace injury.
- Examining mental health service use and mental health recovery trajectories following occupational injury.
- Evaluating integrated occupational rehabilitation and return-to-work programs.
- Using linked EMR and administrative health data to understand health system utilization before and after workplace injury. The successful candidate will have advanced training in epidemiology, health services research, population health, biostatistics, data science, occupational health, or a related discipline, and will contribute to peer-reviewed publications, conference presentations, grant applications, and knowledge translation activities. You will report to the Occupational Health Data Lead, Dr.

Karen

Tu. The position is available immediately and is full-time on a 12-month fixed-term basis, with the possibility of renewal based on mutual agreement.

On a practical level, you will

- Leading the development and maintenance of a large occupational health research database using data from an integrated care program.
- Designing and implementing data extraction, cleaning, validation, and quality assurance processes for occupational health EMR data.
- Developing linked research datasets incorporating occupational rehabilitation records, radiology reports, diagnostic imaging data, emergency department visits, hospital admissions, physician claims, and primary care EMR data.
- Working with clinicians, health system partners, and data custodians to establish and maintain a sustainable occupational health research data platform.
- Conducting research on occupational injury care pathways, care coordination, timeliness of care, return-to-work outcomes, loss-of-earnings transitions, and mental health outcomes following workplace injury.
- Applying advanced quantitative methods, including longitudinal cohort analyses, predictive modeling, machine learning, sequence analysis, and health services research methodologies.
- Conducting literature reviews and evidence syntheses related to occupational health, disability prevention, rehabilitation, and health system performance.
- Collaborating with occupational health clinicians, rehabilitation providers, healthcare organizations, researchers, and policy stakeholders to translate research findings into improvements in care delivery and worker outcomes.
- Analyzing and interpreting complex linked administrative and EMR data sources.
- Preparing manuscripts for peer-reviewed journals and presenting findings at national and international conferences.
- Preparing technical reports, policy briefs, grant applications,



and knowledge translation products.
- Supervising graduate students, trainees, and other research personnel.

Qualifications

- PhD in Epidemiology, Health Services Research, Biostatistics, Public Health, Data Science, Occupational Health, Health Informatics, Family Medicine Research, or a related discipline.
- Demonstrated expertise in quantitative research methods and analysis of large healthcare datasets.
- Experience working with electronic medical record (EMR) data, health administrative data, or linked population-based datasets.
- Experience with statistical software such as R, SAS, SQL, Python, Stata, or equivalent.
- Experience preparing manuscripts for submission to peer-reviewed journals.
- Strong scientific writing and presentation skills.
- Ability to work independently while managing multiple projects and collaborating with multidisciplinary teams.
- Strong organizational and project management skills.
- Excellent verbal and written communication skills.
- Ability to communicate complex data and findings to clinicians, health system leaders, researchers, policy-makers, and community stakeholders.

Preferred

Qualifications

- Experience working with occupational health, workers' compensation, rehabilitation, disability management, or return-to-work research.
- Experience building or managing large clinical or administrative research databases.
- Experience with primary care EMR data, hospital administrative data, diagnostic imaging datasets, or provincial health administrative databases.
- Experience conducting data linkage studies and longitudinal cohort analyses.
- Knowledge of machine learning, predictive analytics, artificial intelligence, or advanced causal inference methods.
- Demonstrated interest in occupational health policy, workplace injury prevention, rehabilitation, and health system improvement. This fellowship provides a unique chance to build a first-of-its-kind linked occupational health data platform while leading innovative research at the intersection of occupational medicine, rehabilitation, epidemiology, health services research, and data science.

What We Offer Working at NYGH means working with a dynamic team of fellow healthcare providers, staff, and volunteers in one of Canada’s leading hospitals.This is a Full Time Temporary position of 24 months with 8 hour shifts, Day shifts in the Research and Innovation Department.

We offer a highly competitive total compensation package which may include benefits, pension, vacation pay, or pay in lieu of benefits, when applicable. If you were searching for more reasons to consider joining the wonderful team at NYGH, check out some features of our Total Rewards package by visiting nygh.on.ca

How To Apply

Think you're the right person for the job? Here's your first chance to show us why:

- Ensure to meet the deadline - only applications received by the closing date will be considered.
- We will review all applications and will contact those selected for an interview.

Closing Statement At North York General, we are committed to fostering an inclusive and accessible environment. We are dedicated to building a workforce that reflects the diversity of the community in which we live, including those with disabilities.

North York

General is committed to providing accommodations in all parts of the hiring process. If you require an accommodation, we will work with you to meet your needs.

📌 Post Doctoral Fellow, Occupational Health Data and Health System Research - FTT (Toronto)
🏢 North York General Hospital
📍 Toronto