Staff - Non Union
M&P - AAPS
AAPS Salaried - Statistical Analysis, Level C
Scientific Lead for Computational Biology and AI in Precision Health
Turvey Laboratory | Department of Paediatrics | Faculty of Medicine
$8,305.08 - $12,952.33 CAD Monthly
The Compensation Range is the span between the minimum and maximum base salary for a position. The midpoint of the range is approximately halfway between the minimum and the maximum and represents an employee that possesses full job knowledge, qualifications and experience for the position. In the normal course, employees will be hired, transferred or promoted between the minimum and midpoint of the salary range for a job.
June 22, 2026
Note: Applications will be accepted until 11:59 PM on the Posting End Date.
This position is subject to the satisfactory completion of required background checks
Job End Date
June 30, 2027
This position is subject to the satisfactory completion of required background checks.
Note: Only the Full-Time Compensation Range is displayed on the job posting details advertised on the UBC Career sites.
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.
Position Summary
This position is designed for a senior computational biologist with extensive expertise (10+ years) in multi-omics data integration, artificial intelligence, systems biology, translational research, and collaborative data-driven research environments. The role requires advanced scientific leadership in the development and implementation of integrative analytical frameworks, including interpretable machine learning approaches, that support large-scale immunology, infectious disease, inflammation, and precision medicine initiatives within the Turvey Laboratory.
The position is particularly suited to candidates with demonstrated expertise in high-dimensional biological data integration, computational analysis of complex datasets, statistical and machine learning modelling, and the architectural design of scalable, reproducible analytical workflows in collaborative research environments.
The Scientific Lead for Computational Biology and AI in Precision Health is a senior scientific and technical position within the Turvey Laboratory, responsible for leading the integration, interpretation, and operationalization of complex multi-omics datasets generated through translational and clinical immunology research programs. The lab has a particular focus on identifying monogenic causes of human disease. The role provides leadership in computational biology and artificial intelligence strategy, research facilitation, and interdisciplinary collaboration across projects involving bulk and single cell genomics, transcriptomics, epigenomics, proteomics, metabolomics, microbiome, and clinical metadata.
Working closely with investigators, clinicians, bioinformaticians, trainees, collaborators, and external partners, the successful candidate develops and implements scalable computational frameworks and AI-assisted workflows that support discovery science, biomarker development, precision medicine initiatives, and grant-funded research activities. The position plays a central role in enabling high-impact, data-driven research within the laboratory and across collaborative networks.
The Scientific Lead for Computational Biology and AI in Precision Health exercises a high degree of initiative, independence, and professional judgment in managing scientific priorities, developing advanced analytical and machine learning workflows, establishing rigorous data governance, stewardship, and reproducibility standards, and supporting strategic research planning.
Organizational Status
The position reports directly to the Principal Investigator, Dr. Stuart Turvey, and operates with a high degree of independence. The successful candidate serves as a strategic liaison, working collaboratively with laboratory staff, research associates, postdoctoral fellows, graduate students, clinicians, institutional bioinformatics cores, and national and international collaborators.
The successful candidate may provide technical direction, mentorship, and supervision to technical staff, trainees, and personnel involved in computational data analyses, as well as overseeing research coordination activities.
Work Performed
Scientific Leadership and Computational Analyses
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Architects and directs the design, development, and implementation of integrated multi-omics data analyses and artificial intelligence strategies across laboratory research programs.
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Develops and deploys cutting-edge computational approaches, including interpretable machine learning models, for integrating high-dimensional genomic, transcriptomic, epigenomic, proteomic, metabolomic, microbiome, and clinical datasets.
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Interprets complex, large-scale biological data to support translational research objectives in immunology, infectious diseases, inflammation, and precision medicine.
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Acts as a scientific advisor to investigators and collaborators on study design, advanced computational analytical methodology, statistical considerations, and downstream data interpretation.
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Identifies emerging technologies, state-of-the-art machine learning and computational biology tools, and analytical methods to maintain the laboratory’s competitive edge.
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Establishes and drives strategic partnerships with internal and external institutional stakeholders to support large-scale collaborative research initiatives.
Research Facilitation and Project Management
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Coordinates, prioritizes, and manages data integration activities across multiple concurrent research projects.
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Establishes operational timelines, priorities, deliverables, and rigorous quality standards for computational and analytical workflows.
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Serves as a multi-disciplinary bridge, facilitating communication between wet-lab researchers, clinicians, computational scientists, and collaborators.
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Supports grant development, contributing to research strategy, study design, preliminary analyses, budgeting, and methodological sections.
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Contributes to manuscript and potentially leads preparation, scientific presentations, technical reports, and knowledge translation activities.
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Participates in strategic institutional planning related to research infrastructure, high-performance computing (HPC), and data management.
Data Management and Computational Infrastructure
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Designs, implements, and maintains production-grade, scalable, and reproducible analytical pipelines, workflows, and documentation.
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Oversees the stewardship, quality control, harmonization, and integration of data assets.
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Establishes, mandates, and promotes best practices in institutional data governance, reproducibility, secure data management, version control (Git), and containerized reproducibility (e.g., Docker/Singularity).
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Works with institutional IT and HPC teams to optimize and scale cluster infrastructure and cloud-based analytical environments.
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Evaluates, benchmarks, and deploys specialized software tools, databases, and platforms to enhance laboratory research capabilities.
Training, Mentorship, and Collaboration
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Provides technical mentorship and training to laboratory personnel, trainees, and collaborators in computational biology and multi-omics data analyses.
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Supports capacity building within the laboratory by developing analytical standards, protocols, and educational resources.
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Fosters an inclusive, interdisciplinary culture of collaboration and promotes effective knowledge sharing across diverse research teams.
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Represents the laboratory in high-level collaborative meetings, international workshops, and scientific working groups.
Compliance and Professional Standards
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Ensures all computational and data storage activities strictly comply with institutional policies, ethical standards, privacy regulations, and data-sharing agreements.
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Maintains current knowledge of relevant scientific, technical, and regulatory developments in computational biology and AI in precision health.
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Performs other senior-level duties consistent with the qualifications and classification of the position.
Consequence of Error/Judgement
The work performed by this senior leadership position has a direct, critical impact on the research quality, outcomes, scientific interpretation, and long-term strategic direction within the Turvey Laboratory and its collaborative research programs. Errors in data handling, analytical design, computational workflows, statistical analysis, or interpretation of complex biological datasets could significantly affect research conclusions, scientific publications, collaborative initiatives, clinical translation, regulatory compliance, and future funding opportunities.
The position is expected to exercise a high degree of independent judgment, scientific leadership, discretion, and technical expertise in planning, prioritizing, and executing complex analytical and research facilitation activities with minimal supervision. Decisions made by the position may influence research priorities, methodological approaches, resource allocation, collaborative partnerships, and the overall scientific direction of projects. Failure to maintain appropriate standards in data governance, reproducibility, project coordination, or scientific interpretation could adversely affect the reputation of the laboratory, collaborating investigators, and the institution.
Supervision Received
The position reports directly to Dr. Stuart Turvey, Principal Investigator of the Turvey Laboratory. The role is executed with a high degree of independence and responsibility for decisions related to study design, analytic execution, multi-omics integration workflows, and mentoring of trainees and staff. The Scientific Lead for Computational Biology and AI in Precision Health acts as a peer advisor, providing expert scientific, technical, and methodological counsel to the PI and the broader research team, including contributions to strategic planning, study design, and analytical direction for ongoing and future research programs.
Supervision Given
This position holds formal responsibility for providing technical direction, mentoring, and advanced training to trainees, undergraduate and graduate students, junior computational analysts, and post-doctoral fellows within the Turvey Laboratory and affiliated research programs. The Scientific Lead for Computational Biology and AI in Precision Health provides technical direction and oversight on project-based data and computational analyses, ensuring rigor, reproducibility, and alignment with study objectives.
The role contributes to the ongoing development of the team’s analytical capacity through training, knowledge transfer, and development of standardized workflows and best practices in multi-omics analysis. The position may lead or coordinate analytic working groups across projects or partner institutions, fostering collaboration and consistency in methodological approaches.
Minimum Qualifications
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Post-graduate degree in Statistics. Minimum of five years of related experience in integrative analysis, or the equivalent combination of education and experience.
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Willingness to respect diverse perspectives, including perspectives in conflict with one’s own.
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Demonstrates a commitment to enhancing one’s own awareness, knowledge, and skills related to equity, diversity, and inclusion.
Preferred Qualifications
Education
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PhD in bioinformatics, computational biology, systems biology, biostatistics, computer science, genomics, immunology, or a related discipline preferred.
Experience
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Minimum of 10 years of post-PhD related experience in computational biology, bioinformatics, or multi-omics research environments, preferably within academic, industry, or translational research settings.
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Experience integrating multiple high-dimensional biological datasets.
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Experience supporting collaborative interdisciplinary research programs.
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Experience with scientific project coordination and research facilitation.
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Equivalent combinations of education and experience may be considered.
Skills and Abilities
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Demonstrated expertise in computational biology, bioinformatics, systems biology, and multi-omics integration.
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Strong background in the analysis and interpretation of high-dimensional biological datasets, including analysis for monogenic disorders.
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Extensive experience developing bioinformatics pipelines, computational tools, and reproducible analytical frameworks for large-scale omics datasets.
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Advanced programming and scripting expertise in R, Python, and Bash.
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Extensive experience working with high-performance computing (HPC) environments (e.g., Slurm), cloud-based infrastructure, workflow management systems, and containerized solutions (e.g., Docker/Singularity)
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Experience working with high-performance computing environments, cloud-based infrastructure, workflow management systems, and containerized computational workflows.
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Experience integrating bulk and single-cell genomic, transcriptomic, epigenomic, proteomic, and clinical datasets in translational research settings.
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Experience collaborating with interdisciplinary teams including clinicians, immunologists, computational biologists, statisticians, and research trainees.
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Strong scientific publication record and demonstrated ability to contribute to high-impact collaborative research initiatives.
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Experience supporting grant development, collaborative research networks, and strategic scientific planning.
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Demonstrated ability to provide mentorship, technical leadership, and scientific guidance within research teams.
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Ability to exercise sound judgment, initiative, diplomacy, and discretion.
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Excellent organizational, interpersonal, and communication skills.
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Ability to work independently and collaboratively in a fast-paced research environment.
Specialized Technical Expertise
The successful candidate is expected to demonstrate expertise in several of the following areas:
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Multi-omics data integration and systems biology
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Genome analysis
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Computational biology and bioinformatics analysis
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Machine learning and predictive modelling in biological systems
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Bulk and single-cell omics analysis
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Biological pathway and network analysis
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Statistical genomics and computational immunology
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Reproducible research and workflow automation
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Development and optimization of bioinformatics software tools
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Scientific programming and data visualization
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Collaborative translational research environments
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Integration of clinical and biological datasets
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Data stewardship, governance, and reproducibility practices
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Scientific communication and interdisciplinary collaboration
Working Conditions
Work is performed primarily in an office and research environment within a large academic health research institution. The position may require occasional flexibility in work hours to accommodate project deadlines, collaborative meetings, or research priorities.
Equity Statement
The University of British Columbia and the Turvey Laboratory are committed to fostering an inclusive and equitable workplace and encourage applications from all qualified individuals, including members of groups that have been historically, persistently, or systemically marginalized.
