Postdoctoral Researcher in Machine Learning for Multimodal Healthcare AI
Postdoctoral Researcher in Machine Learning for Multimodal Healthcare AI
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Job Description
Union: Non-Union
Number of Vacancies: 1
Site: Toronto General Hospital Research
Department: Multi organ Transplant
Reports to: Dr. Mamatha Bhat
Hours: 37.5
Shifts: Monday to Friday
Status: Temporary Full-Time
Closing Date: October 31 2025
Position Summary
Were seeking a Postdoctoral Researcher in Machine Learning / Computer Science to help build the next frontier of deep learning multimodal fusion and longitudinal modeling in clinical medicine. This unique position offers the opportunity to work at the intersection of AI healthcare and translational science tackling some of the most complex challenges in transplant medicine and liver disease. The candidate would be co-supervised by both Dr. Mamatha Bhat (clinician) and Dr. Divya Sharma (Computer Science).
- Build generative and predictive models using longitudinal multimodal patient data including clinical variables labs imaging pathology and multi-omics.
- Design and deploy foundation model-inspired architectures for real-time clinical applications.
- Incorporate causal inference and counterfactual modeling to guide treatment simulations and improve decision-making.
- Develop clinician-facing software tools that embed your ML models into UHNs digital ecosystem.
- Contribute to high-impact research publications funding proposals and collaborative innovations across AI and medicine.
- innovations across AI and medicine.
Duties
1. Data Integration & Preprocessing
- Preprocess and harmonize large-scale longitudinal datasets comprising structured (clinical/lab) and unstructured (imaging pathology molecular) data.
- Develop reproducible pipelines for multimodal data ingestion from diverse health system and research sources (e.g. EHRs biobanks imaging repositories).
2. Machine Learning & Model Development
- Design train and validate predictive and generative models leveraging deep learning causal inference and time-aware architectures.
- Build foundation model-inspired pipelines for patient trajectory modeling treatment response simulation and risk stratification in liver disease and transplantation.
3. Translational AI Tool Deployment
- Translate research outputs into clinician-facing software applications ensuring integration into UHNs digital ecosystem.
- Build user-friendly interpretable tools with real-time capability to support decision-making in complex clinical workflows.
4. Scientific Discovery & Collaboration
- Co-lead hypothesis-driven translational research in collaboration with clinicians data scientists and health system partners.
- Explore novel computational strategies for multimodal fusion and disease modeling.
5. Knowledge Mobilization & Scholarly Output
- Contribute to high-impact publications presentations and grant proposals that bridge AI and healthcare.
- Document technical workflows and model development for reproducibility and knowledge sharing.
6. Supervision & Mentorship
- Engage with and support junior trainees including students and analysts contributing to shared project goals and team culture.
- Collaborate closely with supervisors Dr. Mamatha Bhat and Dr. Divya Sharma through regular joint meetings and milestone planning.
7. Learning & Growth
- Stay current on state-of-the-art developments in machine learning generative modeling and precision medicine.
- Adapt models and methods to evolving project requirements in a fast-paced interdisciplinary environment.
Qualifications :
- A recent (or soon-to-be) PhD graduate in Machine Learning Computer Science Bioinformatics or related fields.
- Fluent in Python and experienced with deep learning frameworks like PyTorch or TensorFlow.
- Familiar with (or excited to learn) deep generative models causal ML transformer architectures foundational models and multimodal learning.
- A collaborative and curious researcher with a strong publication record excellent communication skills and a passion for translational AI in medicine.
Additional Information :
Why join UHN
In addition to working alongside some of the most talented and inspiring healthcare professionals in the world UHN offers a wide range of benefits programs and perks. It is the comprehensiveness of these offerings that makes it a differentiating factor allowing you to find value where it matters most to you now and throughout your career at UHN.
- Competitive offer packages
- Government organization and a member of the Healthcare of Ontario Pension Plan (HOOPP access to Transit and UHN shuttle service
- A flexible work environment
- Opportunities for development and promotions within a large organization
- Additional perks (multiple corporate discounts including: travel restaurants parking phone plans auto insurance discounts on-site gyms etc.)
Current UHN employees must have successfully completed their probationary period have a good employee record along with satisfactory attendance in accordance with UHNs attendance management program to be eligible for consideration.
All applications must be submitted before the posting close date.
UHN uses email to communicate with selected candidates. Please ensure you check your email regularly.
Please be advised that a Criminal Record Check may be required of the successful candidate. Should it be determined that any information provided by a candidate be misleading inaccurate or incorrect UHN reserves the right to discontinue with the consideration of their application.
UHN is an equal opportunity employer committed to an inclusive recruitment process and workplace. Requests for accommodation can be made at any stage of the recruitment process. Applicants need to make their requirements known.
We thank all applicants for their interest however only those selected for further consideration will be contacted.
Remote Work :
No
Employment Type :
Full-time
Employment Type
Full-time
