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activity. · Computational or bioinformatics experience for analysis of omics data. Required Application Materials: 1. Cover letter describing your background, programming experience, and research interests
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longitudinal consistency and data quality, including parameter tracking, protocol versioning, and rigorous QC frameworks Implementing, validating, and extending image-processing and analysis pipelines
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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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developments in sensor design, dataset transmission, data analysis, and numerical modeling to distinguish between normal and abnormal features. Here, the goal is to develop machine learning algorithms
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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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. Leading the analysis of single-cell and spatial transcriptomics data. Applying and developing the analysis framework for spatiotemporal modeling. Publication in top-tier journals, and apply and obtain
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, neural differentiation, and bioinformatic analysis while addressing fundamental questions about how chromosomal imbalances cause developmental disorders. This work has direct translational potential, as
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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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Strong quantitative and analytical skills Experience in either experimental neuroscience (e.g., in vivo neurophysiological recordings, behavioral training) or computational data analysis (e.g., spike
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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