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Note: Applications will be accepted until 11:59 PM on the Posting End Date.
Job End Date
January 31, 2027This is a part-time role at 0.4 FTE, approx. 14 hours per week, and the pay will be pro-rated accordingly.
At UBC, we believe that attracting and sustaining a diverse workforce is key to the successful pursuit of excellence in research, innovation, and learning for all faculty, staff and students. Our commitment to employment equity helps achieve inclusion and fairness, brings rich diversity to UBC as a workplace, and creates the necessary conditions for a rewarding career.
Job Summary
The Genome Canada Transplant Consortium (GCTC) is an international program linking 22 universities in Canada, the US, EU and UK which is developing advanced genomic, immunologic and pharmacologic technologies in the field of organ transplantation. The GCTC Knowledge Integration core in Precision Medicine has an opportunity for an experienced Biostatistician to work with an active international research team using advanced methodologies and machine learning. This position offers excellent opportunities for academic scholarship, research leadership and publication in translational and clinical research projects.
The successful candidate will work closely with the Principal Investigator and members of the research team and will be involved in research projects that will require skills in a design and implementation of advanced statistical methodologies and analysis, mathematical simulations, machine learning and data science techniques, and multi-purpose data linkages.
Organizational Status
The successful candidate will work closely with the lead investigator at the Vancouver General Hospital site and will act as a liaison between research team members located at local and international sites.
Work performed
Participate as a member of research team to provide statistical expertise for the design, execution and analysis of genomic, translational and clinical studies.
Design and develop advanced statistical models and methodologies for complex biomedical studies.
Provide expert consultation on study design, model selection, and simulation-based evaluations.
Provide statistical, data linkage and management consultation to the research team through leadership in data linkage and statistical analysis in cross-divisional multi-disciplinary projects.
Perform statistical modeling and mathematical simulation of research data for introducing new statistical methodologies and study designs.
Provide leadership in the security and integrity of all research databases and research activities.
Develop detailed data management and statistical analysis plans that include, but are not limited to study design, data linkage and management, study objectives, statistical methodologies and analysis, knowledge transition to internal and external project research community.
Advise and execute data retrieval and management of databases for cohort-based epidemiological, clinical, genomic and transitional studies.
Consult on design and development of multiple data analyses, including data availability, choice of metrics and measures and development of strategy and implementation of data linkages and integration of multi-institutional clinical and administrative databases; oversee data quality and automation of recurring processes.
Respond to consulting requests requiring expertise in statistical methodologies and procedures.
Provide statistical contributions to data mining operations and algorithm development.
Prepare statistical methodology sections for research protocol development, reports, grants proposals and publications based on clinical findings and evidence-based outcome analysis.
Gather, analyze, and interpret research data providing conclusions and recommendations, using a variety of established and newly developed statistical software.
Respond to a variety of questions from research staff regarding study design, interpretation, statistical methodology and software.
Manage multiple tasks and work with multidisciplinary team. Communicate technical concepts (via both written and oral presentations) to non-statisticians.
Other duties as assigned.
Consequences of Error/Judgement
The candidate will be working with data derived human subjects. As such he/she will be expected to strictly adhere to standard operating procedures to maintain the integrity of the data and hence provide reproducible results. The candidate will exercises professional judgment and initiative in assessing design and testing approaches, and will be accountable for the delivery and reliability of his/her own work
Supervision Received
The candidate is expected to work independently of setting up, maintaining, optimizing and running the statistical analysis processes. Candidate will work independently under general direction of Lead project Investigator. The candidate is expected to provide regular research activity updates and present research findings to the team members.
Supervision Given
Throughout the study the candidate may give technical guidance to team members (technicians, students, research fellows and co-investigators) on how to use specific statistical methods and analysis techniques. Advice and mentor junior analysts and research staff in statistical test.
Minimum Qualifications
Post-graduate degree in Statistics. Minimum of three years of related experience in research analysis, or the equivalent combination of education and experience.
- Willingness to respect diverse perspectives, including perspectives in conflict with one’s own
- Demonstrates a commitment to enhancing one’s own awareness, knowledge, and skills related to equity, diversity, and inclusion
Required Qualifications:
PhD Degree (equivalent) or higher in biostatistics, informatics or data sciences or equivalent combination of education and experience. Expertise in clinical sciences, including data management, study design, statistical methodologies and analysis, algorithm development, and reporting using SAS and / or R programming languages, and experience with machine learning and large data analytics are important assets. A working knowledge of medical terminology and medical experience either in a clinical and/or research setting is preferred. Knowledge of Research Ethics Board and Human subject protection regulations would be an asset.