Postdoctoral Researcher

Responsibilities

• 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, including structural and diffusion MRI
• Perform statistical modelling, validation, and calibration of predictive models
• Contribute to the development of clinically interpretable outputs such as structured reports and atrophy maps
• Collaborate closely with clinical partners to ensure usability and clinical relevance
• Draft manuscripts, abstracts, and grant applications
• Present research findings at meetings and conferences
• Mentor graduate and undergraduate trainees

Requirements

• PhD in neuroscience, biomedical engineering, computer science, medical physics, or a related field obtained within the past 5 years
• Strong programming skills in Python, R, or MATLAB
• Experience with machine learning and statistical modelling
• Experience with neuroimaging analysis, preferably MRI-based methods
• Demonstrated scientific productivity through peer-reviewed publications
• Strong analytical, problem-solving, and communication skills

Preferred Qualifications

• Experience with voxel-based or morphometry-based neuroimaging analyses
• Experience developing end-to-end pipelines or tools for clinical use
• Experience with model deployment such as APIs, GUIs, or clinical software pipelines
• Familiarity with neuroimaging toolkits like ANTs, FSL, FreeSurfer, or SPM

About the Company

UHN is Canada’s #1 hospital and the world’s #1 publicly funded hospital. As Canada's top research hospital, UHN is a national and international source for discovery, education, and patient care, with major research in neurosciences, cardiology, oncology, and genomic medicine.