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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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protection data in a cohort of over 10 000 dyads of young mothers and their children to investigate health factors associated with the continuity of child maltreatment across generations in Quebec, Canada. Job
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technical equipment, including confocal microscopes, data storage servers, computational workstations, and high-content imagers. They will also support the day-to-day operations of the laboratory, which
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evidence from diverse sources, analyze international survey data, and contribute to the development of a conceptual framework that captures the multi-level and intersectional nature of stigma. Findings from
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computational approaches for high-dimensional data analysis. https://www.epelmanlab.com/ http://www.uhnresearch.ca/researcher/slava-epelman @EpelmanLab This role has direct mentorship and guidance in grant
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therapeutic strategies to promote these beneficial immune states. Position Overview The Postdoctoral Fellow will lead multi-omic data generation, integration, and analysis to dissect immune–tumour interactions
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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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programs in the United States. Fulbright Canada offers various scholarship awards within this program, with further information on the various award opportunities made available through the Canada-US
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work in the biological sciences, and who are dedicated to pursuing a career in academic research. Please visit this video overview of the CASI program for more information from former Program Officer Dr
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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