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: Synthesize small molecules, produce samples of proteins and nucleic acids Characterization using a variety of biophysical methods including in silico modeling, ITC and UV-Vis spectroscopy Perform medicinal
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with PERL’s mission Our Science & Evidence learning tracks: Pandemic prevention & risk anticipation (e.g. primary and secondary prevention, surveillance innovation, spillover risk modeling, zoonoses
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Nature Careers | Vancouver South Shaughnessy NW Oakridge NE Kerrisdale SE Arbutus Ridge, British Columbia | Canada | about 1 month ago
. For those interested, there is also an option to learn and use in vivo cancer or diabetes models. Collaborative and Supportive Environment: You will collaborate closely with experienced scientists and
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Grant (ORF-RE (external link) ). The SSHRC-funded project was launched in 2021 and the objectives of this research are to: 1) expand conceptual models for intergenerational partnerships; 2) investigate
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approaches (based on functional programming abstractions) to optimize the implementation of machine learning models and other digital signal processing algorithms on a specific FPGA architecture to fit within
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in live or fixed organisms, cells or tissues - Experience with data analysis in Python, R or similar - Experience working with animal models AND - Experience with mass spectrometry, including sample
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) Postdoctoral Researchers are Research Fellows recognized by the Quebec government employed at McGill with a valid Doctoral degree (PhD or MD) for a maximum of 5 years after obtaining their Doctoral Degree
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Grant (ORF-RE (external link) ). The SSHRC-funded project was launched in 2021 and the objectives of this research are to: 1) expand conceptual models for intergenerational partnerships; 2) investigate
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Status Reports to the Principal Investigator (Dr. Leluo Guan). Will work with Post-Doctoral Fellows to establish omics data storage, transfer and management, and develop machine learning models
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have expertise in working with animal disease models, single-cell and spatial RNA sequencing technology, and a solid understanding of the CNS immune landscape. Additionally, applicants should have at