Develop AI-based clinical phenotyping methods at McGill University using medical text, structured symptoms, and health data. This full-time position is based in Quebec.
The Postdoctoral Researcher will support the hEDS*Omics Study within McGill’s Canada Excellence Research Chair in Genomic Medicine. The work targets recognition of potentially undiagnosed, misdiagnosed, or delayed hEDS and HSD cases. You will combine clinical notes, ICD codes, HPO terms, omics resources, and structured phenotypes to identify diagnostic patterns.
Key Responsibilities:

Develop and evaluate AI pipelines for hEDS and HSD case identification
Extract and normalize phenotypes from unstructured medical records
Compare candidate cases with diagnoses, criteria, chart reviews, or experts
Validate sensitivity, specificity, predictive value, and clinical usefulness
Prepare scripts, documentation, reports, figures, manuscripts, and grant materials
Requirements:

PhD in computational biology, bioinformatics, computer science, data science, or related field
Experience with clinical, biomedical, genetic, EHR, or administrative data
Experience with large language models, NLP, medical text mining, or clinical AI
Strong Python and/or R programming skills
Familiarity with medical terminology, ICD codes, phenotype extraction, or HPO
Apply AI, clinical phenotyping, Python, and health-data expertise to hEDS/HSD identification research at McGill University.

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AI Clinical Phenotyping Postdoctoral Researcher