Machine Learning Research Engineer

AAPS Salaried - Scientific Eng., Machine Learning Engineer/Scientist
Bashashati Laboratory | School of Biomedical Engineering | Faculty of Medicine
6, $8,986.00 CAD Monthly
We anticipate the successful candidate will begin in the position in January 2026.
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.
The School of Biomedical Engineering (SBME) at the University of British Columbia (UBC) is a partnership between the Faculties of Applied Science and Medicine, established in 2017. The School is a nucleus for education and training, research, and innovation in biomedical engineering, creating new knowledge, new academic and training programs, and fostering translation and innovation. Its vision is to transform health and healthcare for all, achieved through innovative research and education at the convergence of engineering, medicine and biology. Through collaborative, innovative, and interdisciplinary approaches and building on UBC's academic and research excellence, the School of Biomedical Engineering aspires to be a global leader in biomedical engineering research, education and translation. The SBME has two locations on Vancouver's campus, the Gordon B Shrum building and the Biomedical Research Centre (BRC). For more information about the School of Biomedical Engineering, please visit
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The computational cancer biology and pathology artificial intelligence team (AI in Medicine Lab) at the University of British Columbia (UBC), seeks a temporary Machine Learning Engineer/Scientist on a 1 year term. This position is located at the Gordon B Shrum building and entails implementing machine learning-based analysis infrastructure and software for cancer imaging, drug development, and bioinformatics.
The position reports to the Principal Investigator or a designate in the AI in Medicine Lab. 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.
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
Supervision Given
May give work assignments to technical staff. Undergraduate degree in Engineering or Applied Science. Demonstrates a commitment to enhancing one's own awareness, knowledge, and skills related to equity, diversity, and inclusion.
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.