Postdoctoral Researcher

Responsibilities

• 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
• PhD in neuroscience, biomedical engineering, computer science, medical physics, or a related field (obtained within the past 5 years) required
• Strong programming skills (e.g., Python, R, MATLAB, or similar)
• Experience with machine learning and statistical modelling
• Experience with neuroimaging analysis (MRI-based methods preferred)
• Experience with voxel-based or morphometry-based neuroimaging analyses an asset
• Experience developing end-to-end pipelines or tools for applied or clinical use an asset
• Experience with model deployment (e.g., APIs, GUIs, or clinical software pipelines) an asset
• Familiarity with neuroimaging toolkits (e.g., ANTs, FSL, FreeSurfer, SPM) an asset
• Ability to work independently and lead projects
• Strong analytical and problem-solving skills
• Excellent written and verbal communication skills
• Demonstrated scientific productivity (e.g., peer-reviewed publications)
• Interest in translational and clinically impactful research
• Why join UHN?
• Competitive offer packages
• Government organization and a member of the Healthcare of Ontario Pension Plan (HOOPP https://hoopp.com/ )
• Close access to Transit and UHN shuttle service
• A flexible work environment
• Opportunities for development and promotions within a large organization
• Additional perks (multiple corporate disc

Benefits

Additional Information

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

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