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Field
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transcriptomic profiling of cell lines and human primary tissues. This work will provide important advances in our understanding of human blood stem cell biology in the context of normal and neoplastic
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-throughput functional genomics data sets on the genome, epigenome, and transcriptome in disease-relevant tissues/cells and use of computational approaches to integrate and analyze this data to identify
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presentation, HLA expression, interferon-response signaling, HER2, or tumor-intrinsic immune evasion. Experience with epigenetics, chromatin biology, transcriptomics, DNA methylation, ATAC-seq, RNA-seq, or other
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fibrosis, in vitro and in vivo testing therapeutic candidates, scRNAseq, spatial transcriptomics, confocal and electron microscopy imaging, flow cytometry, and standard biochemical/molecular approaches. Our
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cell immunology, mucosal immunology, and cancer immunology using animal models and single-cell multiomics/spatial transcriptomics approaches. This postdoctoral researcher will combine wet-lab molecular
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conditions by applying omics technologies (e.g., genomics, transcriptomics), validation of gene expression using quantitative reverse transcriptase polymerase chain reaction, and bioinformatic analyses
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genomics data sets on the genome, epigenome, and transcriptome in disease-relevant tissues/cells and use of computational approaches to integrate and analyze this data to identify the molecular components
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cancer progression in the West lab in the Department of Pathology at Stanford. Successful candidates will use a combination of spatial transcriptomics and highly multiplexed imaging to understand how
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of muscle hypertrophic growth; 2) identifying the glucose transporter(s) activated by resistance training in muscle; and 3) examining the connections between glucometabolic flux and the muscle transcriptome
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of high-throughput imaging and molecular data (i.e., genome, transcriptome, epigenome, and more). The methods would be able to systematically integrate biomedical/biological knowledge to improve