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). Postdoctoral Fellow, Multimodal Machine Learning Role Overview The Postdoctoral Fellow will develop techniques to build a foundation model of human neurotypes by integrating cognitive task performance
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diagnostic "buckets" with a continuous, high-dimensional AI foundation model of human neurotypes. To achieve the massive global scale required, data collection will be driven by a mobile and browser
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predicting short-term convective hazards. The model development will be aided by synthesizing observational data and high-resolution numerical simulations to gain new conceptual insights on cloud life cycles
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Summary: Work on the project to build a statistical model that predicts stability of a given heteroaromatic silicon-fluoride acceptor to survive in the body Scientific writing Mentoring graduate
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. Retrieval-augmented generation, agentic AI workflows, prompt engineering, or model evaluation. Clinical phenotype extraction from free text. Electronic health records, OMOP, FHIR, ICD-code-based
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ecosystem Experience in edge AI, model optimization, or deployment of AI models on-device Strong programming skills and experience building robust research or product-grade software Ability to work
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governance and emergency management landscape (an asset, either in Canada or elsewhere with a similar model). The postdoctoral researcher must be resident in Québec to perform work for this position
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consult their website for collective agreement https://www.aerum-amure.ca McGill University is strongly committed to diversity within its community and especially welcomes applications from racialized
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/Postdocs (PSAC) bargaining unit. For further information, consult the text of the collective agreement, which can be found at: https://www.mcgill.ca/hr/files/hr/collective_agreement_-_post_docs_-_2023-2026_