Research Associate-Term

Date Posted: 05/22/2026

Req ID: 48208

Faculty/Division: Faculty of Arts & Science

Department: Data Sciences Institute

Campus: St. George (Downtown Toronto)

Existing Vacancy: Yes

Description

DESCRIPTION

Founded in 1827, the University of Toronto has evolved into Canada’s leading institution of learning, discovery and knowledge creation. We are proud to be one of the world’s top research intensive universities, driven to invent and innovate. U of T is home to some of the world’s most talented thinkers, inventors, innovators, and educators, who are advancing knowledge and making critical discoveries for a healthier, more sustainable, prosperous, and secure future.

The Data Sciences Institute (DSI) is a highly specialized research initiative at the University that draws on world-class research expertise across multiple academic divisions, affiliated hospitals, regional, national, and international academic partners, and commercial organizations. Our mission is to provide the leadership and capacity to catalyze the transformative nature of data sciences across disciplines, leveraging and strengthening U of T’s preeminence in data sciences and AI to solve some of the most complex and pressing problems facing society. DSI supports and promotes the flow of methodologicaladvancements such as data integration, novel methodology, visualization methods and facilitates the training of new generations of interdisciplinary trainees.

DSI aims to unify and galvanize the core strengths of Toronto’s data science community building capacity for data and computational-based research projects and training by being the focal point for the coordination of data science activities and partnerships to further elevate UofT’s global stature.

About This Opportunity

The Data Sciences Institute at the University of Toronto invites applications for a Research Associate (Limited Term) for an up to 5 year appointment to support VITAL, a new federally funded initiative focused on enabling secure, near real-time access to hospital data for research and innovation. This will include more than 160 hospitals across Ontario, Alberta, and Quebec, serving over 20 million Canadians. It lays the foundation for Pan-Canadian data sharing for research and is positioned to become one of the most innovative and valuable health data resources in the world. The anticipated start date is June 1, 2026.

A Research Associate is intrinsically involved in research projects where they contribute, by way of their academic expertise, to the projects directed by the VITAL Principal Investigators. As part of this national initiative, the Data Sciences Institute will develop a suite of methods for federated analysis of electronic health record (EHR) data.

The Research Associate will lead the development, implementation and management of the methods for federated statistical analysis of EHR data and provide tailored tools for users of the federated data network. The Research Associate will also work closely with researchers on various biomedical applications using the federated data network.

Applicants should apply online at the link below and include a cover letter, curriculum vitae, and three reference names with their contact addresses and phone numbers.

Any questions regarding this position should be directed to Prof. Jessica Gronsbell at j.gronsbell@utoronto.ca. All materials should be received by the closing date for full consideration.

All qualified candidates are encouraged to apply; however, Canadians and permanent residents will be given priority.

Minimum Qualifications

Education: PhD in statistical sciences, computer sciences, applied mathematics or data sciences, biostatistics, biomedical informatics, or related specialty.

Experience

• A minimum of 4 years of experience in the analysis of EHR data (structured and unstructured) and collaborative biomedical research
• Demonstrated expertise required in federated statistical inference methods required, ideally in context of EHR
• Proficiency with computing and reproducible research workflows required
• A strong publication record in methodological and applied statistics
• Experience in scientific writing and communication
• Demonstrated capacity to work in both independent and interdisciplinary research settings

Skills

• Statistical analysis and study design: Developing analytic plans, conducting analyses within a federated data network, and reporting results
• Programming: SQL, Python, and R
• Command of EHR data curation and standardization, including familiarity with ontologies such as the Unified Medical Language System (UMLS) and the Observational Medical Outcomes Partnership (OMOP) common data model
• Strong strategic, analytical, and problem-solving skills
• Strong interpersonal and project management skills to facilitate effective research collaborations and timely and professional deliverables
• Strong written and oral communication skills, with the ability to effectively communicate statistical analyses to clinical audiences
• Natural language processing experience or knowledge is a plus
• Medical image analysis is a plus
• Experience working with big data and building data and analytical pipelines is a plus

Closing Date: 06/26/2026, 11:59PM ET

Employee Group: Research Associate

Personnel Subarea:Research Assoc

Appointment Type: Budget - Term

Schedule: Full-Time

Pay Scale Group & Hiring Zone: R01 -- Research Associates (Limited Term): $53,520 - $100,350

Job Category: Administrative / Managerial

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Diversity Statement

The University of Toronto embraces Diversity and is building a culture of belonging that increases our capacity to effectively address and serve the interests of our global community. We strongly encourage applications from Indigenous Peoples, Black and racialized persons, women, persons with disabilities, and people of diverse sexual and gender identities. We value applicants who have demonstrated a commitment to equity, diversity and inclusion and recognize that diverse perspectives, experiences, and expertise are essential to strengthening our academic mission.

As part of your application, you will be asked to complete a brief Diversity Survey. This survey is voluntary. Any information directly related to you is confidential and cannot be accessed by search committees or human resources staff. Results will be aggregated for institutional planning purposes. For more information, please see http://uoft.me/UP.

Accessibility Statement

The University strives to be an equitable and inclusive community, and proactively seeks to increase diversity among its community members. Our values regarding equity and diversity are linked with our unwavering commitment to excellence in the pursuit of our academic mission.

The University is committed to the principles of the Accessibility for Ontarians with Disabilities Act (AODA). As such, we strive to make our recruitment, assessment and selection processes as accessible as possible and provide accommodations as required for applicants with disabilities.

If you require any accommodations at any point during the application and hiring process, please contact uoft.careers@utoronto.ca.

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