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and transmission network modeling is useful but not necessary, as long as the candidate is willing to learn on the job. A list recent and past research projects on electricity market design undertaken
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) signaling. The Huttenhain lab integrates cutting-edge MS-based proteomics, functional genomics, imaging, and other molecular biology techniques to profile the spatiotemporal nature of GPCR signaling networks
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: The Pain Intelligence Lab The Stanford Center for Population Health Sciences Interdisciplinary collaborations within Stanford School of Medicine Opportunities to engage with national networks in rheumatology
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chain network analysis and geospatial modeling. The successful candidate will have strong data science skills, including experience working with large, complex data from varied sources, and machine
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cell fate decisions, particularly during early neural development or during the epithelial-to-mesenchymal transition (EMT) in cancer. Our recent work reveals that coding sequences (CDS) and their cognate
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algorithmic performance. For instance, the scheduling problems that an electric grid operator faces will change daily, but not drastically: although demand will vary, the network structure will remain largely
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superb quantitative background, strong coding skills (e.g., Python, R), expertise in infectious disease modeling across multiple pathogens, expertise with large datasets and statistical analysis, and high
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sensor integration. Strong coding and debugging skills. Excellent communication, documentation capabilities and a demonstrated track record of publication. An enthusiasm for developing new measurements
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accomplishments, (b) Your broader research interests, and (c) why you are interested in working with us A sample of data analysis code (published or unpublished) A representative writing sample (published
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. At single cell level, how does the same genome give rise to thousands of different cellular phenotypes in the brain? 2. At the tissue level, how do gene networks orchestrate intercellular communication