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contaminants), food science, and food analysis. Proficiency in different areas of chromatography, high-resolution mass spectrometry and data analysis. At least two first-authored English papers (or three if co
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field. Demonstrated experience with single-cell and/or spatial transcriptomic analysis (Scanpy, Seurat, Squidpy, etc.). Strong programming proficiency in Python and R; experience with machine-learning
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instrumentation for clouds and precipitation (e.g., cloud radar, passive or active satellite sensors) Experience with instrument simulators. Experience with machine learning techniques. Strong programming skills
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access to large-scale neuroimaging and language datasets, advanced analytical tools, and a dynamic, multidisciplinary environment. The researcher is supported in developing independent projects, building
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Matlab, Python, or R programming experience. - A background in fMRI data analysis. - Excellent oral communication and interpersonal skills. - Ability to work effectively independently and in a team
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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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to work in Canada and willing to work in the province of Quebec at the campus where the position is based / located. McGill University is an English-language university where most teaching and research
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Program research grant, this project brings together complementary expertise of the Zhulyn (Canada), Lagha (France), vanOudenaarden (Netherlands) and Kelleher (US) labs for a team-driven, multidisciplinary
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related field. Proficiency in one or more of the following: in vivo electrophysiology, two-photon imaging, animal surgery, behavioral design, programming languages (Python/MATLAB), and data analysis
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communities. McGill implements an employment equity program and encourages members of designated groups to self-identify. Persons with disabilities who anticipate needing accommodations for any part of