8 data-science Postdoctoral positions at McGill University

  • McGill University | Old Montreal, Quebec | Canada | about 9 hours ago

    resources. Collaborate with internationally recognized leaders in computational neuro-oncology. Thrive in The Neuro’s open-science environment, fostering data sharing and interdisciplinary innovation. Join

  • McGill University | Canada | 15 days ago

    ) microscopy, FLIM, STED, lattice lightsheet microscopy, fluorescence correlation spectroscopy (FCS), image processing and analysis and spectral imaging. More information about the ABIF can be found at: http

  • McGill University | Canada | 2 months ago

    integration under the D2R umbrella. This project will develop the postdoc’s expertise in applied AI/data workflows, interdisciplinary collaboration, reproducible science, experimental planning, project

  • McGill University | Old Montreal, Quebec | Canada | about 1 month ago

    workflows. Qualifications PhD in Computational Biology, Genomics, Biomedical Engineering, Neurosciences, or related fields. Proven expertise in single-cell or spatial transcriptomic/proteomic data analysis

  • McGill University | Old Montreal, Quebec | Canada | 3 months ago

    . Collaborate with internationally recognized leaders in computational neuro-oncology. Thrive in The Neuro’s open-science environment, fostering data sharing and interdisciplinary innovation. Before applying

  • McGill University | Old Montreal, Quebec | Canada | about 1 month ago

    : Department of Atmospheric and Oceanic Sciences Postdoctoral Researcher - Spaceborne Doppler radar science and applications Spaceborne Doppler radar observations play a critical role in atmospheric and Earth

  • McGill University | Canada | 3 months ago

    : The RA will perform experiments to support multiple projects in the lab. The type of work will include, but is not limited to, animal behaviour, biochemical analyses, molecular and cell biology experiments

  • McGill University | Canada | about 1 month ago

    spatio-temporal generative models, and multimodal foundation models—including vision-language MLLMs and agentic AI frameworks—for longitudinal MRI and clinical data. Fellows will help build next-generation

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