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, various cutting-edge experimental and computational approaches in the areas of functional genomics, cell biology, biochemistry, single-cell/spatial multi-omics, data mining, drug screening, and disease
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part of our team, you will leverage state-of-the-art single-cell, spatial and organoid technologies in a collaborative and interdisciplinary environment. Research focus We welcome candidates with a
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multi-disciplinary approaches to answer these key questions including; immunology, oncology (in vitro model-organoid systems, ex vivo tissue culture), microbiology, next generation sequencing (16S seq
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(TMJ) degeneration and pain, and salivary gland degeneration. The lab uses mouse and human iPSC/organoid models equipped with genomic, single cell RNA sequencing, spatial transcriptomics, tissue clearing
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for pediatric diseases. Our research focuses on how genetic variants contribute to diseases during early development and on developing mechanism-driven therapeutics. While animal models have advanced our
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Nature Careers | Vancouver South Shaughnessy NW Oakridge NE Kerrisdale SE Arbutus Ridge, British Columbia | Canada | about 2 months ago
increasingly utilizes big data, satellite imagery, register data, and advanced methods such as deep learning and neural networks to address major societal challenges related to spatial inequalities and
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We invite applications from highly motivated and talented researchers for a 2-year postdoctoral position in advanced skin models, cellular immunology, and spatial transcriptomics, starting August 1
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. Successful applicants will work together as part of an international team of experts at four sites to apply cutting-edge approaches in high-resolution, single-molecule imaging; single-cell Ribo-seq and spatial
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for pediatric diseases. Project Description: Our research focuses on how genetic variants contribute to diseases during early development and on developing mechanism-driven therapeutics. While animal models have
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explores novel myeloid cell-based immunotherapy against intraperitoneal metastasis of ovarian cancer using mouse models and patient samples as well as state-of-the-art technologies such as spatial multi