Staff - Non Union
M&P - AAPS
AAPS Salaried - Scientific Eng., Level A
Machine Learning Engineer/Scientist
Human Resources Support | Department of Pathology and Laboratory Medicine | Faculty of Medicine
$6,251.00 - $8,986.00 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 23, 2026
Note: Applications will be accepted until 11:59 PM on the Posting End Date.
Job End Date
August 3, 2027
The anticipated start date for this position is August 4, 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 computational cancer biology and pathology artificial intelligence team (AI in Medicine Lab; aimlab.ca) at the University of British Columbia (UBC), seeks a Machine Learning Engineer/Scientist on a 1-year term (renewable contingent on funding and performance). This position is located at the Gordon B Shrum building as well as Jack Bell Research Center and entails implementing machine learning-based analysis infrastructure and software for cancer imaging, drug development, and bioinformatics.
Organizational Status
The position reports to the Principal Investigator or a designate in the AI in Medicine Lab.
Work Performed
- Conducts in-depth literature reviews on medical imaging (digital pathology and clinical imaging), genomics and drug analysis, evaluates complex machine learning applications, develops hypotheses on data collection, model architecture, and training strategies and assesses feasibility and technical requirements for integrating findings into existing projects.
- Designs and develops machine learning computer models (i.e. algorithms) for medical imaging, bioinformatics (i.e genomics data including single cell and spatial omics) and drug development applications.
- Performs analysis of tissue images of cancer and protein-ligand binding affinity using novel machine learning with advanced algorithms such as Alphafold3 for molecule processing and foundation models for image processing.
- Modifies and tunes existing programming modules to integrate with image management platform, enabling the execution of in-house AI models on imaging data.
- Analyses results of machine learning algorithms, documents and prepares reports accordingly.
Consequence of Error/Judgement
Exercises judgment in the design and specifications of new machine learning software and algorithms and makes recommendations for the adoption of specific algorithms.
Supervision Received
Works independently within task objectives. Works within well defined guidelines and procedures, but exercises judgment in establishing priorities and carrying tasks through to completion; new or unusual problems are referred to supervisor.
Supervision Given
May give work assignments to technical staff.
Minimum Qualifications
Undergraduate degree in Engineering or Applied Science. Minimum of one year of related experience, 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
Ideal candidates should have a solid grasp of:
- Intermediate algorithms and data structures.
- High-level programming languages (Python, JavaScript, etc).
- Knowledgeable with containerization software (Docker, Kubernetes, Singularity).
- Digital pathology experience and/or genomics and or/ drug development.
- Basic computer vision and image processing techniques.
- Experience with Agile Development.
- Expertise in cloud software development, particularly with ML applications.
- Familiarity with AWS services.
