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opportunities to use approaches including GWAS, Mendelian randomization, transcriptomics and multi-omics analyses alongside functional genetic studies in Drosophila. Particular areas of interest include
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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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adipose tissue using single-cell and spatial transcriptomic approaches. Mapping neural pathways connecting adipose tissue with the peripheral and central nervous systems. Recording and perturbing neural
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disorders, particularly autism, using novel computational approaches, neuroimaging-derived brain circuit fingerprints and transcriptomic signatures. A second project focuses on developing multimodal
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to create “A Spatial Transcriptomic Atlas of Embryo-Endometrial Crosstalk During Implantation and Human Embryo Development”. This position is funded by a new collaborative grant between the laboratories of Dr
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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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at the time of application. Experience in molecular and cell biology techniques, preferably in single cell sorting (FACS), scRNA-seq, spatial transcriptomics and very strong multi-omic data analysis skills
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profiling. More broadly, this work aims to establish a new experimental framework for spatial multi-omic analysis that complements existing spatial transcriptomics technologies. Responsibilities
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Expertise in primary cell isolation and culture, FACS, confocal imaging, and mouse genetics is preferred Experience with transcriptomics and programming language suitable for computational analysis (e.g. R