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) 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
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an initial one-year appointment and potential for renewal. This Postdoctoral fellow position is part of the CIHR funded Zika virus (ZIKV) Individual Participant Data (IPD) Meta-analyses (MA) Phase II and the
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in Prof. Reza Salavati's lab, at Macdonald Campus, McGill University. Position Summary: The postdoc will contribute to the D2R (Data-to-Reality) applied research program aimed at developing novel data
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harmonize different data streams. Lead and co-author manuscripts, reports, and presentations. Collaborate with interdisciplinary and international research partners. Qualifications PhD (completed or near
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& Evidence: Investigating applied policy and programming questions to strengthen pandemic prevention, such as early warning systems, crisis data infrastructure, and overlooked drivers of vulnerability
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are: Create favourable circumstances for the development of a field of research and a community of research on access to justice for OLMCs Produce scientific data for and with the access to justice stakeholders
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workflows. Qualifications PhD in Computational Biology, Genomics, Biomedical Engineering, Neurosciences, or related fields. Proven expertise in single-cell or spatial transcriptomic/proteomic data analysis
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(BBB) dysfunction and edema in brain cancer, a major source of morbidity in the disease. Using radiomics, single-cell, and spatial omics, the project integrates imaging and molecular data to better
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that postdoctoral researchers receive the guidance and resources necessary to thrive in both academic and applied research settings. Qualifications: PhD in Neuroscience, Psychology, Psychiatry, Biomedical Engineering
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. Qualifications: PhD in machine learning, with experience in applications in computer vision or medical image analysis. Strong publication record in top venues (e.g., CVPR, MIDL, MICCAI, IPMI, PAMI, TMI, MIA