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with researchers both at Stanford and the U.S. Census Bureau. The position is open to recent graduates of PhD programs in economics, statistics, sociology or related data science fields, preferably with
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. Strong background in computational analysis and immunological studies. Experience with data analysis for single-cell or spatial methods is highly desirable. Excellent communication and interpersonal skills
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, biostatistics, data science, or a related field are encouraged to apply. A candidate who has recently submitted the PhD thesis or is about to submit the thesis is encouraged to apply. A strong computational
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. Tissue sectioning for advanced spatial transcriptomic analysis. Leading the analysis of single-cell and spatial transcriptomics data. Applying and developing the analysis framework for spatiotemporal
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workflows for data cleaning, linkage, and analysis within Stanford’s secure computing environment. Collaborate with multidisciplinary teams of clinicians, economists, and policy researchers. Prepare
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pathology. The successful candidate will gain expertise in stem cell biology, genome engineering, neural differentiation, and bioinformatic analysis while addressing fundamental questions about how
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translational oncology, and a vibrant research community that spans discovery to clinical implementation. Specific Responsibilities include: experimental design, data acquisition, data processing, statistical
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schools, are affiliates. The institute pursues its objectives through seed funding, hosting interdisciplinary centers, organizing convenings, and leadership training. Required Qualifications: A PhD in data
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be the focus of the first year: improving lead detection of paint (ICP-OES, XRF and colorimetry) and managing the analysis of a representative survey collecting over 10,000 samples of spices, soil and
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screening, high-content imaging, or functional assays of sensory or neuronal activity. · Computational or bioinformatics experience for analysis of omics data. Required Application Materials: 1. Cover letter