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proteomics, structural biology, and molecular biology to define new modes of GPCR signaling. We are particularly interested in candidates with strong backgrounds in proteomics and/or structural biology and/or
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groups from Stanford and beyond working on complementary approaches to T cell recognition. Our group provides an intellectually rich environment, with scientists applying genetics, proteomics and machine
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, or equivalent) conferred by the start date. 2. Proficiency in R/Python. 3. Experience with spatial proteomic/transcriptomic data analysis. 4. Growth mindset and motivation to advance our understanding of breast
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biological systems, inflammatory diseases, or diverse clinical patient sample data. Familiarity with processing and analyzing multi-omics datasets (e.g., metagenomics, metabolomics or proteomics) integrated
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generating and working with large datasets (e.g., tissue RNA sequencing, single cell RNAseq, spatial proteomics or transcriptomics) Technical experience with primary cell culture and cell culture
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proteomics, circulating microRNA, etc.). Please note that this position has no wet-lab component. Applicants holding a PhD, MD, or MD/PhD are welcome to apply. Non-US citizens and non-US residents are also