Entry Level Bioinformatics Software Engineer Jobs in British Columbia

Staff - Non UnionJob CategoryM&P - AAPSJob ProfileAAPS Salaried - Statistical Analysis, Level AJob TitleBioinformatics ScientistDepartmentAparicio Laboratory | Department of Pathology and Laboratory Medicine | Faculty of MedicineCompensation Range$6,438.50 - $9,255.58 CAD Monthly

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Posting End DateAugust 17, 2026

Note: Applications will be accepted until 11:59 PM on the Posting End Date.

Job End Date

August 16, 2027

The anticipated start date for this position is Aug 17, 2026. The term is for one year with the possibility of extension.

In your application please include (1) a cover letter, and (2) a CV or resume.

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 Department of Pathology and Laboratory Medicine of the University of British Columbia has a position open immediately for a bioinformatics scientist to work within the Aparicio lab (https://aparicio.molonc.ca). Located at the BC Cancer Research Institute, within the Department of Basic and Translational Research; Molecular Oncology, our interdisciplinary team is comprised of over 30 researchers, research scientists, lab technicians, computational biologists, software developers and engineers. We are seeking a creative, experienced, and dedicated individual with experience in genomic and image data analysis to play a key research role in the bioinformatics analysis of computational genomic research data, applied to translational oncology and drug development.

The bioinformatics scientist will work closely with other bioinformaticians and research scientists within the Aparicio Lab and other collaborative labs to carry out computational analysis and data exploration in projects addressing the molecular understanding of breast cancer through the analysis of single-cell genomics, spatial genomics, transcriptomics and imaging datasets. Following directions from the scientific research leads, you will carry out bioinformatics solutions to computational and statistical inquiries in support of research projects. You will be responsible for the production and analysis of data from automated high-throughput analysis pipelines. You will be responsible for the design, testing and development of new bioinformatics workflows for the lab.

You will work on-site at BC Cancer Research Institute, working closely with software developers, students and researchers operating at the leading edge of the field of cancer genomics. The Aparicio Lab has made meaningful advances in the understanding of tumour evolution, translational oncology and drug development. Data, software platforms and computational methods developed in the lab will be used by world-leading scientists at BC Cancer and international collaborators to gain insight into how cancers initiate, develop and acquire resistance to treatment. More information on the department and research we conduct can be found here https://aparicio.molonc.ca
Organizational Status
The Aparicio Lab is located in the Department of Basic and Translational Research at BC Cancer Research Institute in Vancouver, British Columbia, Canada. The candidate will report directly to Dr. Samuel Aparicio or designate
Work Performed

• Conduct advanced bioinformatics analysis of single-cell genomics, spatial genomics, transcriptomics and imaging datasets generated by the Aparicio lab

• Own, develop, implement, test, and optimize bioinformatics workflows and computational pipelines for ongoing and emerging research initiatives
• Utilize programming, scripting, and command-line tools in high-performance computing environments to execute, troubleshoot, and enhance computational analyses of large-scale biological datasets
• Prepare and submit publications based on single cell spatial datasets
• Provide expert technical advice and guidelineto trainees and other lab members on spatial single cell analysis
• Collaborate with internal and external research partners to coordinate data generation activities, curate research datasets, manage data submissions, and ensure successful delivery of computational analysis outcomes within project timelines.
• Participate in selection and training of co-operative education students that may join the lab

Consequence of Error/Judgement
The work is complex and requires a high level of training, tasks are assigned and the incumbent exercises a considerable amount of responsibility, initiative and judgment in determining their work schedule to achieve those tasks. Incorrect decisions or actions may damage the reputation of the laboratory, lead to a loss of credibility in this field, and be financially costly.
Supervision Received
The successful applicant will work under minimum supervision. From time to time, the Principal Investigator or designate may provide specific instructions on unusual problems or new project outlines. This position will report to the Principal Investigator.
Supervision Given
The successful applicant may assist in overseeing the technical work of students and trainees.
Minimum Qualifications
Post-graduate degree in Statistics. Minimum of two 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

Preferred Qualifications

Expertise with command-line interfaces and scripting in UNIX operating systems

Expertise with handling next-generation sequencing (NGS) and imaging data

Expertise with statistical modelling and the design of geospatial statistical software

Excellent communicator and professionalism

Experience designing and creating analysis workflows and pipelines

Proven publication record and bioinformatics research experience

Experience with scientific high performance computing environments

Experience with large scale multi-omics research, specifically spatial genomics data in the form of Imaging Mass Cytometry, Expansion Sequencing, 10x Xenium platform and MERFISH

Experience with human disease and cancer genomics