Postdoctoral Research Fellow Full-time NEW

Postdoctoral Research Fellow

The Edwin S. H. Leong Centre for Healthy Aging (ELCHA) is seeking a highly motivated Postdoctoral Research Fellow for the Canadian Microbiome Mapping Initiative (CMMI). This will be a 100% FTE (full-time) position for a one-year term with the possibility of renewal. Work will be performed on-site at the Edwin S. H. Leong Centre for Healthy Aging at the UBC Vancouver campus with the possibility of a hybrid work agreement.

The primary goal of the CMMI is to develop an integrated multi 'omics platform to investigate the biological mechanisms and pathways by which the microbiome influences health and disease. This will include investigations into healthy aging as well as validation of the platform in clinical contexts, beginning with Parkinson's disease. The successful candidate will serve as a data manager to liaise between the project's different data generating and database development teams and facilitate the integration, analysis, and interpretation of datasets. This role is part of a broader vision to spearhead data integration and analysis of a growing multi-'omic dataset designed to study healthy aging, Parkinson's Disease, and other age-related conditions.

The CMMI is a large, collaborative initiative involving investigators in the ELCHA, other UBC research centres, and external collaborators.

Under the supervision of CMMI PI Dr. Michael Kobor, and with scientific and technical guidance from Dr. Emilia Lim and the CMMI Data Analysis and Integration Committee, the candidate will contribute to data analysis, data integration, and interpretation across diverse datasets. The position will also work alongside the CMMI Project Manager for day-to-day operations, prioritization, and project delivery.

The position also works in close collaboration with CMMI investigators, bioinformaticians, laboratory personnel, and research staff. The position will provide technical supervision and mentorship to computational biology trainees, technicians, and graduate students, as appropriate.

The following work will be performed:

• Pipeline development: Design, develop, implement, and maintain reproducible multi-omics data integration pipelines, including data processing, harmonization, and statistical analysis workflows.
• Data translation: Lead technical data activities across laboratories and omics groups; works with investigators, bioinformaticians, and technicians to identify available data and analytical need; and translate these into technical specifications for database and infrastructure development. Consult key stakeholders to capture data management requirements, such as data planning, collection, processing and compliance, pertaining to the Faculty of Medicine data platforms, software, and tools in support of good data management practices.
• Data quality: Perform quality control and ensure the integrity of research datasets, collaborating with contributing laboratories to resolve technical issues.
• Methodological leadership: Provide expert guidance on analytical strategy, model selection, and integration approaches across multi-omics datasets, exercising professional judgement in assessing and refining analytical methods.
• Conduct statistical, bioinformatics, and AI/ML-based analyses to interpret relationships between datasets, health, and disease.
• Software evaluation: Evaluate and implement tools and software for data analysis, visualization, and integration.
• Technical data support: Serve as a technical data partner, assisting investigators, trainees, and staff with data processing, analysis, and workflow implementation under project guidance.
• Produce and maintain technical documentation, including pipeline workflows, algorithms, QC procedures, and SOPs to ensure reproducibility.
• Communicate technical progress, analytical findings, and workflow updates to collaborators through meetings, presentations, and contributions to manuscripts.
• Scholarly leadership: Lead the preparation of manuscripts, abstracts and technical sections of grant applications, and contribute to study-level interpretation of findings.
• Knowledge dissemination: Present research findings at conferences, seminars, and other scientific meetings.
• Innovation and advancement: Identify opportunities to improve or extend analytical pipelines and integration methods as the project evolves, incorporating emerging best practices in multi-omics and data science.
• Performs other related duties as required.

The incumbent exercises independent technical judgment in the development and maintenance of data integration pipelines, analytical workflows, and quality control procedures, with major technical decisions reviewed in consultation with the Project Manager and the Data Integration and Analysis Committee.

Errors in judgment may result in data loss, compromised data integrity, or delays in research activities, potentially affecting project timelines, collaborations, and scientific outputs. Failure to adhere to data security and quality standards could lead to breaches of participant confidentiality or biased and incomplete results, with reputational and operational consequences for the investigators, the Centre, and the University.

Works with considerable independence under scientific and technical guidance from the CMMI Data Integration and Analysis Committee, and the general direction of the CMMI Project Manager. Exercises independent technical judgment within established project objectives, standards, and data governance requirements. Keeps the team informed of the status of work in progress.

Provides technical guidance and mentorship to computational biology trainees, research assistants, technicians, graduate students, and other research personnel as required. May oversee and coordinate the work of junior staff and students on data curation, analysis, and pipeline-related tasks, ensuring adherence to established workflows and quality standards.

Minimum qualifications:

• PhD in bioinformatics, computational biology, statistics, computer science, or a closely related field.
• Around 2–3 years of relevant post-doctoral or equivalent experience in bioinformatics, multi-omics integration, or computational analysis.
• Experience with automated pipeline development, multi-omics dataset integration, and reproducible workflows.
• Advanced proficiency in R, Unix/Linux environments, databases, and version control (Git).
• Experience with AI/ML applications for data analysis.
• Demonstrated ability to mentor and collaborate.
• Strong written and verbal communication skills
• Ability to work independently while collaborating with multidisciplinary teams.
• Demonstrated ability to effectively engage with colleagues and the researcher community.
• 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.

Preferred qualifications:

• Experience with high-performance or cluster computing.
• Experience producing reusable software packages or analytical pipelines.
• Familiarity with visualization and interactive tools (RShiny, Plotly, Power BI).
• Knowledge of molecular and cellular biology.

Opportunities and impact:

• Advance the frontiers of multi-omics integration and analysis using a dataset of over 600 participants.
• Lead high-impact publications in collaboration with field experts.
• Attend and present research at international conferences focused on healthy aging, genomics, AI, and/or microbiome research.
• Translate fundamental discoveries into clinically actionable strategies over the course of the project.
• Access a highly collaborative research environment across UBC laboratories, research institutes, and clinical partners to support career development.
• Engage with ELCHA, gaining access to an interdisciplinary community, collaborative opportunities, and participation in seminars, events, and scientific initiatives within the Faculty of Medicine-approved Centre for Healthy Aging, supporting professional development and visibility within the healthy aging research space.
• Gain mentorship and support from the CMMI Data Integration and Analysis Committee as well as national leaders in epigenetics, AI, and microbiome research (Dr. Michael Kobor, Dr. Raymond Ng, Dr. Emilia Lim, Dr. Keegan Korthauer, Dr. Brett Finlay, etc.) for pursuing external funding and fellowship opportunities.