Position number: 38307 Term Department of Anesthesiology, Periop. & Pain Med. Rady Faculty of Health Sciences

Posting start date: October 2, 2026 Advertised until: November 1, 2026 or until filled

Full-time: Yes

Permanent: No

Start date: November 1, 2026

For more information please contact: Taj Shakir - Farooqui - [email protected]

The Department of Anesthesiology, Perioperative and Pain Medicine invites applications for a Full Time / 1.0 FTE Research Associate position, commencing November 1, 2026, or on a date mutually agreed upon. Salary will be commensurate with experience and qualifications.

The Research Associate will support research initiatives under the purview of Dr. Thomas Mutter and the Anesthesiology research program with following key responsibilities:

- Work with clinician-investigators to translate research questions into clear cohort definitions, variable specifications, data requirements, and analysis plans for the purposes of protocol development, ethics submissions and grant applications.
- Provide advanced data management and analysis support for departmental research, with a major focus on studies using MCHP and other administrative or population-based health data.
- Conduct approved data management, programming, and analysis in the MCHP and other secure research environment, subject to applicable privacy, data-access, retention, and disclosure requirements.
- Develop, run, and maintain programs in SAS and other statistical analysis software to query, extract, import, clean, recode, transform, and analyze research data within approved data environments.
- Create analytic cohorts and derived variables using documented inclusion and exclusion criteria, index dates, lookback and washout periods, follow-up and censoring rules, clinical definitions, administrative-data algorithms, and appropriate temporal relationships among exposures, covariates, and outcomes.
- Develop and maintain data dictionaries, codebooks, programming specifications, annotated code, and other documentation needed to support reproducible analyses.
- Perform systematic data-quality checks, investigates discrepancies, validates derived variables and analytic outputs, and documents assumptions and limitations.
- Develop and implement statistical analysis plans appropriate to the research question and study design, including selection of outcome measures and statistical models, covariate and confounder specification, assessment of interaction/effect modification, handling of missing data, model diagnostics, and prespecified sensitivity or subgroup analyses where appropriate and within the incumbent's expertise.
- Independently use local and online resources to problem solve data management and analysis issues.
- Consult with MCHP analysts/programmers, biostatisticians and other specialized resources when issues remain unresolved or are beyond acquired skill set.
- Provide guidance to residents, graduate students, and research staff on data management, analysis, reproducibility, and interpretation of results. Appropriately advise on the implications of data limitations, missingness, bias, confounding, and model assumptions.
- Contribute data, methods, results, publication-quality tables, and figures to abstracts, presentations, reports, study protocols, grant applications, manuscripts and manuscript revisions.
- Ensure that reported results are traceable to validated data and code.
- Review and, where appropriate, revises data-management or analytic work prepared by trainees, research staff, collaborators, or external programmers.
- Perform other related senior research duties consistent with the education, experience, and scope of the position

About the Research Program

Anaesthesiology researchers conduct primarily clinical research including some studies using large databases that require programming and analytical support. These include several studies in collaboration with the Manitoba Centre for Health Policy (MCHP) (https://umanitoba.ca/manitoba-centre-for-health-policy/). These studies often involve resident trainees in the department.

MCHP maintains a renowned data repository of the Manitoba population that includes decades of routinely collected health administrative data and other social service databases. Further information about the research initiatives can be obtained from Department of Anesthesiology,



Perioperative and Pain Medicine | Max Rady College of Medicine | University of Manitoba The successful candidate will have PhD in epidemiology, biostatistics, health services research, population health, data science, public health, or another directly related quantitative discipline.

OR A Master's degree in a directly related discipline may be considered where the candidate has substantial advanced experience managing and analyzing complex health research data and can work independently at a senior research level.

Preferred qualifications include

EXPERIENCE

- Experience using SAS for data management, programming, and statistical analysis, including data step programming, the SAS macro facility, and PROC SQL applied to large longitudinal files, is required.
- Experience working with Manitoba Centre for Health Policy (MCHP) data, Manitoba administrative health data, or a comparable population-based data repository or secure research environment (e.g., ICES, Population Data BC, Alberta Health Services, SAIL Databank, CPRD) is strongly preferred.
- Experience developing analytic cohorts from large, complex health or administrative datasets, applying inclusion and exclusion criteria, deriving variables, and working with longitudinal or linked datasets is required.
- Demonstrated experience with data cleaning, quality assurance, validation, documentation, and management of complex research datasets is required.
- Applied experience selecting, implementing, and interpreting statistical methods used in observational clinical, epidemiologic, or health services research, including multivariable regression methods for common outcome types (e.g., linear, logistic, count, and ordinal models), is required.
- Experience with longitudinal, repeated-measures, mixed-effects, or time-to-event methods is strongly preferred.
- A peer-reviewed publication record demonstrating substantial contribution to data analysis, results, or interpretation is preferred.
- Experience collaborating with clinicians, epidemiologists, programmers, biostatisticians, and multidisciplinary research teams is preferred.
- Experience preparing publication-quality analytic outputs or contributing data, methods, and results to scientific manuscripts is preferred.

SKILLS AND ABILITIES

- Ability to independently develop, run, troubleshoot, and document SAS programs for data management and analysis is required.
- Strong understanding of research data structures, longitudinal data, linkage concepts, variable derivation, missing data, and reproducible analytic workflows is required.
- Strong statistical reasoning, critical appraisal, and problem-solving skills are required.
- Ability to assess data quality, identify inconsistencies and validate analytic outputs is required.
- Ability to clearly and completely document programming assumptions and decisions is required.
- Ability to clearly communicate analytic methods, limitations, and results to clinician-investigators and collaborators with limited programming experience is required.
- Ability to manage multiple datasets, analyses, and project deadlines while maintaining meticulous documentation and attention to detail is required.
- Ability to comply with all personal health information regulatory requirements is required, including PHIA and applicable institutional privacy, de-identification, and disclosure-control (cell suppression) requirements.
- Ability to work independently, exercise sound judgment, and collaborate with investigators, MCHP personnel, programmers, and biostatisticians, including seeking specialized biostatistical or programming input when necessary, is required.
- A satisfactory work record, including satisfactory attendance and punctuality, is required.

OTHER JOB-RELATED QUALIFICATIONS

- Experience with R for data management, analysis, and reproducible reporting is preferred.
- Experience with SQL, Python, REDCap or other relevant analytic or data-management tools is preferred.
- Experience with prediction modelling or model validation, causal or quasi-experimental methods is preferred.
- Experience with MCHP programming conventions and the MCHP Concept Dictionary,



Canadian health administrative data holdings and definitions (e.g., CIHI DAD and NACRS, ICD-10-CA/CCI), or similar population-data environments is preferred.
- Experience with version control (e.g., Git), reproducible research practices, secure computing environments and/or disclosure-control processes is preferred.
- Scientific writing experience, including preparation of methods, results, tables, figures, or responses to data- and analysis-related reviewer comments, is preferred.

Please include the following as part of your application: a curriculum vitae and contact information for three references.

A Review of applications will begin on October 19, 2026 and will continue until filled.

Additional Information:

To enhance our department and create role models for a diverse population of students, we particularly invite application from those who can support and enhance our diversity, including Indigenous peoples, women, racially marginalized persons, persons with disabilities, persons of marginalized sexualities and genders, and those committed to a diverse environment.

The Rady Faculty of Health Sciences is committed to the social justice principles of equity, access & participation and to promoting opportunities in hiring, promotion and tenure (where applicable) for systemically marginalized groups who have been excluded from full participation at the University and the larger community including Indigenous Peoples, Black, racially marginalized communities, disabled persons and those who identify as 2SLGBTQIA (Two Spirit, lesbian, gay, bisexual, trans, questioning, intersex, asexual and other diverse sexual identities).

An inclusive, open and diverse community is essential to excellence and fosters voices that have been ignored or discouraged. To address the Rady Faculty of Health Sciences commitment to equity, access and participation, and in recognition of the underrepresentation of members of historically and currently excluded groups, we take proactive measures including implicit bias training for all hiring panels. We strive for diversity and cultural safety throughout the hiring process (hiring panels, short-list of candidates, interviews).

The University acknowledges the potential impact that Career Interruptions and Personal Circumstances can have on an applicant's record of research achievement. Measures will be taken to ensure that these leaves will be taken into careful consideration during the evaluation process.

We encourage you to self-identity aspects of your identity that position you to bring currently under-represented viewpoints, expertise and forms of excellence to this role.

Additional information:

The University of Manitoba is a driving force of innovation, discovery and advancement. Our momentum is propelled by our campus community – UM faculty, staff and students whose determination and curiosity shape our world for the better. Our teaching, learning and work environment is uniquely strengthened and enriched by Indigenous perspectives. With two main campuses in Winnipeg, satellite campuses throughout Manitoba, and world-wide research, UM’s impact is global.

Discover outstanding employee advantages, experience world-class facilities and join a dynamic community that values reconciliation, sustainability, diversity, and inclusion. We are one of Manitoba’s Top Employers and one of Canada’s Best Diversity Employers. At the University of Manitoba, what inspires you can change everything.

The University of Manitoba is committed to the principles of equity, diversity & inclusion and to promoting opportunities in hiring, promotion and tenure (where applicable) for systemically marginalized groups who have been excluded from full participation at the University and the larger community including Indigenous Peoples, women, racialized persons, persons with disabilities and those who identify as 2SLGBTQIA (Two Spirit, lesbian, gay, bisexual, trans, questioning, intersex, asexual and other diverse sexual identities). If you require accommodation supports during the recruitment process, please contact [email protected] or (phone hidden). Please note this contact information is for accommodation reasons only.

Application materials, including letters of reference, will be handled in accordance with the protection of privacy provisions of "The Freedom of Information and Protection of Privacy Act" (Manitoba). Please note that curriculum vitae will be provided to participating members of the search process.

📌 Research Associate - Health Data management and Analysis (Winnipeg)
🏢 University of Manitoba
📍 Winnipeg