Academic
Job Category
Faculty Non Bargaining
Job Title
Research Associate
Department
Lehman Laboratory | Department of Medical Genetics | Faculty of Medicine (Anna Michelle Lehman)
Posting End Date
August 10, 2025
Note:Applications will be accepted until 11:59 PM on the Posting End Date.
Job End Date
Aug 31, 2026
The expected salary range for this position is $ 84,000.00 CAD to $108,000.00 CAD per annum.
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.
Lehman Laboratory in the UBC Department of Medical Genetics is seeking a full time (1.0 FTE) Research Associate to join our translational research team with an aim to identify causes for increased risk for cardiovascular disorders (eg., cerebral aneurysms, cardiomyopathy, coronary artery disease, or strokes).
The UBC Department of Medical Genetics is a leader in genomic health research. The Lehman laboratory is highly collaborative, working closely with other research labs on large scale projects. Sources of data include large-scale datasets (All of Us, UK Biobank), internal BC-based projects (eg., Silent Genomes; Rare Diseases Discovery Hub), national projects (Care4Rare and Genomics4RD), and smaller lab-specific projects. Much of this work will involve data from Indigenous participants, subject to additional protections in accord with UNDRIP (the UN Declaration on the Rights of Indigenous Peoples). Project rules on data handling and security must be adhered to completely.
RESPONSIBILITIES
Reporting to the Principal Investigator, Dr. Anna Lehman, the incumbent will be responsible for:
Design and run methodologies to identify genetic contributors to disease.
Apply existing polygenic risk scores and linkage programs (MERLIN, SEQLINKAGE) to datasets.
Be willing to attempt creating novel polygenic risk scores, including for low frequency medium-penetrant variants.
Be willing to attempt to incorporate metabolomic data and pre-existing pooled cohort equation data with genetic data for enhanced risk assessment.
Perform GWAS.
Meet with and communicate regularly with the PI to update, plan, and troubleshoot.
Problem solve protocol issues.
Provides supervision and mentorship to trainees and staff. Teach trainees how to use basic Python and R coding to perform beginner – intermediate level analyses.
Present research findings to others.
Prepares content for academic manuscripts, technical reports, research proposals, and presentations.
Performs other project-related duties, as required (eg., logistics).
QUALIFICATIONS
Successful applicants will have:
PhD degree in a life science discipline with bioinformatic, biostatistics, GWAS, and human health experience, or, PhD in a life science plus post-doctoral experience in the aforementioned areas
Fluency in Python, R Studio, Java
Able to work independently, supervise graduate and undergraduate students
Experience in GWAS.
Experience in developing bioinformatic pipelines.
Experience with statistical tools needed for creating risk scores (eg., LASSO, STAARpipeline).
Leadership qualities, strong interpersonal skills, and teaching proficiency.
Effective oral and written communication.
Excellent organizational and record-keeping skills
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.
