Postdoctoral Research Fellow in Machine Learning Genomics,Transcriptomics,and Bioinformatics Job Vancouver area,BC Canada,IT/Tech

Position: Postdoctoral Research Fellow in Machine Learning for Genomics, Transcriptomics, and Bioinformatics
Academic

Job Category

Faculty Non Bargaining

Job Title

Postdoctoral Research Fellow in Machine Learning for Genomics, Transcriptomics, and Bioinformatics

Department

Bashashati Laboratory | School of Biomedical Engineering | Faculty of Medicine (Ali Bashashati)

Posting End Date

April 30, 2026

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

Job End Date

July 15, 2027

The expected pay for this position is $70,000 per year + benefits.

AI and Deep Learning for Genomics, Transcriptomics, and Bioinformatics

The successful candidate will work in the AI in Medicine Lab, applying machine learning to cutting-edge problems in cancer genomics, transcriptomics, spatial transcriptomics, and large-scale bioinformatics. This role focuses on developing and applying AI and deep learning techniques for analyzing high-dimensional omics data, identifying predictive biomarkers, and understanding cancer heterogeneity. Projects include modeling of bulk and single-cell transcriptomic profiles, integrative multi-omics analysis, and the fusion of molecular data with clinical and imaging features.

Organizational Status
The successful candidate will report to the Principal Investigator (Director of AI Research at OVCARE, Dr. Ali Bashashati).

Responsibilities

Designs and implements machine learning models for bulk and single-cell genomics and transcriptomics.

Analyzes spatial transcriptomic datasets to uncover tissue organization and disease states.

Develops integrative models combining genomics with pathology images or time-series data.

Participates in large collaborative studies, manuscript and grant writing.

Mentors junior trainees and coordinate with clinicians and research partners (for senior roles).

Qualifications and requirements

Ph.D. in bioinformatics, computer science, computational biology, or a related field, obtained within the last 5 years by the time of the appointment start date.

Strong experience in deep learning applied to high-dimensional omics datasets.

Familiarity with transcriptomic analysis tools (e.g., Seurat, Scanpy, DESeq2).

Experience with spatial transcriptomics and multi-modal data integration is highly desirable.

Proficient in Python, R, and ML libraries such as PyTorch or Tensor Flow.

Strong communication and collaboration skills; ability to work independently and as part of a team.

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.

How to apply

Important:
Applications will only be reviewed if BOTH of the following steps are completed:

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The expected pay for this position is $70,000 per year + benefits.

The initial appointment will be for 16 months commencing on March 16, 2026 or a mutually agreed upon date with a possibility for extension, subject to satisfactory performance and funding availability.

Questions:

If you have any questions about the positions or the application process, please send contact & .

Review of applications will begin on March 1, 2026 and continue until the position is filled. The anticipated start date for this position is March 16, 2026 or on a date to be mutually agreed.

We encourage applications from individuals of all backgrounds, particularly those from equity-deserving groups. We are committed to creating inclusive spaces that foster innovation through diverse perspectives and experiences.

We invite applications from qualified candidates who share our commitment to employment equity and inclusive excellence, and we welcome applications from candidates belonging to historically, persistently, or systemically marginalized groups:
Indigenous (First Nation, Métis, Inuit) Peoples, racialized persons, persons with disabilities, women, 2

SLGBTQIA+ people, and trans and non-binary people.

The University is committed to creating and maintaining an inclusive and equitable work environment for all members of its workforce. An inclusive work environment presumes an environment where differences are appreciated, recognized, and integrated into current structures, planning, and…


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Postdoctoral Research Fellow in Machine Learning Genomics, Transcriptomics, and Bioinformatics