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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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PhD graduates who are passionate about leveraging computational methods to transform trauma and acute care surgery. Fellows will work at the intersection of clinical medicine, data engineering, and
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. The laboratory applies in vitro and in vivo experimental techniques to study normal and malignant stem cells in aging, cancer, and chronic disease. Additional information on the laboratory can be found on our
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degree (PhD, MD, or equivalent) or Master’s degree in a relevant field (e.g., Computer Science, Biomedical Engineering, Public Health, Surgery) Experience in clinical research, data analysis, or machine
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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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. 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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, 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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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
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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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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