Union: Non-Union
Number of vacancies: 1
New or Replacement Position: New 
Site: Krembil Research Institute
Department: Neuroimaging and Brain Modelling Laboratory
Reports to: Principal investigator
Hours: 37.5 hours per week
Salary Range: $54,902 - $93,333 per annum
Shifts: Monday to Friday
Status: Temporary Full-time  (1 year contract with possibility of extension)
Closing Date: August 13, 2026

Position Summary

Dr. Jürgen Germann’s Neuroimaging and Brain Modelling Laboratory at the Krembil Research Institute, University Health Network, is seeking a highly motivated Postdoctoral Research Fellow to lead a translational neuroimaging project focused on early diagnosis and disease progression modelling in Parkinson’s disease and related disorders.

The successful candidate will play a central role in developing MRI-based, machine learning-driven probability models for differential diagnosis using image-derived features. A key focus will be translating these models into a clinician-facing decision-support tool for real-world implementation. This includes building pipelines that take routine clinical MRI as input and generate patient-specific probabilistic diagnostic outputs to support clinical decision-making.

The position offers a unique opportunity to work at the interface of neuroimaging, machine learning, and clinical translation, with a strong focus on high-impact publications and the development of deployable clinical tools. The work will be conducted in a highly multidisciplinary environment, in close collaboration with Dr. Alexandre Boutet (Neuroradiology) and Dr. Anthony Lang (Neurology; Director of the Movement Disorders Program).

This opportunity will allow you to:

• Lead development of machine learning models for imaging-based diagnostic probability estimation
• Develop and optimize pipelines that generate patient-specific probabilistic predictions from MRI data
• Design and implement a clinician-facing tool for model deployment and integration into clinical workflows
• Analyze large-scale multimodal neuroimaging datasets (structural and diffusion MRI)
• Perform statistical modelling, validation, and calibration of predictive models
• Contribute to development of clinically interpretable outputs (e.g., probability maps, reports)
• Work closely with clinical collaborators to ensure usability and relevance of the tool
• Draft manuscripts, abstracts, and grant applications
• Present research findings at meetings and conferences
•  Mentor graduate and undergraduate trainees
• Collaborate within a highly interdisciplinary team spanning neurology, neuroradiology, medical physics, and data science

Duties

• Lead the development of machine learning models for imaging-based diagnostic probability estimation
• Develop and optimize pipelines to generate patient-specific probabilistic predictions from MRI data
• Design and implement a clinician-facing tool to support model deployment and integration into clinical workflows
• Analyze large-scale multimodal neuroimaging datasets, including structural and diffusion MRI
• Perform statistical modelling, validation, and calibration of predictive models
• Contribute to the development of clinically interpretable outputs (e.g., structured reports, atrophy maps)
• Collaborate closely with clinical partners to ensure usability, interpretability, and clinical relevance of developed tools