Postdoctoral Research Fellow in Machine Learning for Computational Pathology, Medical Imaging, and Clinical Text Analysis

Academic

Job Category

Faculty Non Bargaining

Job Title

Postdoctoral Research Fellow in Machine Learning for Computational Pathology, Medical Imaging, and Clinical Text Analysis

Department

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

Posting End Date

February 28, 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.

Machine Learning for Computational Pathology, Medical Imaging, and Clinical Text

The successful candidate will work on advanced machine learning applications in computational pathology, medical imaging, and clinical text analysis. They will be expected to develop deep learning models for analyzing whole-slide histopathology images, as well as natural language processing (NLP) methods for clinical records such as pathology reports and electronic health data. This position is ideal for candidates passionate about applying AI to real-world healthcare problems in cancer diagnostics and digital pathology.

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

Responsibilities

• Develops deep learning models for classification, segmentation, and risk stratification using histopathology and radiology images.
• Designs NLP models, including large language models (LLMs), for analyzing pathology reports and other clinical text.
• Collaborates with clinical partners to identify and refine real-world use cases.
• Prepares manuscripts, contributes to grant proposals, and presents research findings.
• Supports and mentors junior lab members as appropriate.

Qualifications and requirements

• Ph.D in computer science, bioinformatics, biomedical engineering, electrical engineering or similar, obtained within the last 5 years by the time of the appointment start date.
• Outstanding publication record in top journals and conferences.
• Proven experience in design and implementation of deep learning algorithms.
• Outstanding programming skills in Python.
• Extensive experience working on one or more of the following areas: image processing, machine learning, and patient records.
• Track record of development and implementation of novel machine learning algorithms in the healthcare setting or other spaces.
• Extensive experience in utilizing machine learning libraries such as PyTorch, TensorFlow, and Scikit-learn.
• At least 2 years of experience working with Linux computing clusters.
• Ability to work independently and within a team environment.
• Effective oral and written communication, analytical, and interpersonal skills.
• 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:

• Apply through the
• Fill out this mandatory

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

The initial appointment will be for 16 months commencing 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.

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, 2SLGBTQIA+ 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 decision-making modes. Within this hiring process we are committed to creating an inclusive and equitable process for all candidates (including but not limited to people with disabilities). Confidential accommodations are available on request. If you have any questions regarding accommodations or accessibility during the recruitment and hiring process or for more information and support, please visit UBC’s Centre for Workplace Accessibility website at or contact the Centre at .

We acknowledge that UBC’s Vancouver campus is located on the traditional, ancestral, and unceded territory of thexʷməθkʷəy̓əm (Musqueam) people. As scientists and engineers, we are committed to responsible and respectful research practices on this land.

Benefits

Plan Group Number: 020605Member ID: your 7-digit UBC employee ID number, Need crisis counselling?, Call GreenShield Health at 1-866-424-0770 to chat with a counsellor., Disclaimer, The benefits information on this website is provided as a descriptive summary only. While the University has endeavored to accurately reflect its benefit programs, policies and plans, the information on this website does not create any contractual or other rights between the University and its faculty and staff members. To the extent that there are any conflicts or discrepancies between the benefits information on this website and the benefit plan documents (including group insurance contracts and benefit booklets) or any applicable collective agreement, employment agreement, or UBC policy, the benefit plan documents and collective agreement, employment agreement, or UBC policy will govern in all cases.