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be focused primarily on the development and application of novel computational algorithms to analyze and integrate diverse omics datasets, including bulk and single-cell RNA-seq, ADT-seq, ATAC-seq, DNA
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-cell and spatial-omics research. The ideal fellow will be interested in developing and applying novel computational algorithms to novel datasets generated in the setting of non-neoplastic and neoplastic
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/or experience with large-scale data analysis, algorithm development, or computational modeling. Required Qualifications: Doctoral degree in linguistics, cognitive science, psychology, hearing and
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. Prior Research Fellows have been accepted by PhD programs in computer science, economics, and political science and JD programs at top schools (e.g., Harvard, Stanford, Princeton, Yale). In recent years
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together experts in systems neuroscience, AI, and engineering. This ambitious initiative promises to offer unprecedented insights into the brain's algorithms of perception and cognition while serving as a
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will be focused primarily on the development and application of novel computational algorithms to analyze and integrate diverse omics datasets, including single-cell RNA-seq, spatial transcriptomics and
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different disciplines and mentors Stanford Departments and Centers: Medicine, Biomedical Informatics Research (BMIR) Biomedical Data Sciences Postdoc Appointment Term: 1 year minimum with the option to extend
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. This includes integrating LLMs with structured data sources to develop robust computational phenotyping algorithms and scalable models for real-world evidence generation. The role will involve both method