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University is seeking a postdoctoral scholar to support and lead innovative research at the intersection of rheumatology, pain science, and data science. The successful candidate will work on a portfolio of
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be made better. This is a role for a researcher excited to work with big, messy, real-world data, motivated not just by building models but by improving systems: how clinicians work together, how
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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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expertise in Neuropixels or other large-scale in vivo electrophysiology techniques. An expert neural data analyst may be considered even with minimal animal experience. Required Application Materials: Cover
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verbal. Preferred Qualifications: Experience combining large clinical and research data sets. Interested and comfortable working with pediatric patients with special needs. A track record of publications
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model fairness and model generalizability across multi-institutional electronic health records databases. The researcher will have access to the real-world EHR data from almost 20 sites across
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technology and b) large-scale data collection in a diverse sample spanning over 250 schools across 30 states to answer three significant questions regarding the mechanisms of word reading difficulties such as
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include a PhD in Computer Science, Artificial Intelligence, Natural Language Processing, Human-Computer Interaction, or a closely related field. Candidates should have demonstrated expertise in Large
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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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on hotspot detection. This modeling work is well supported by large-scale primary datasets, including survey-based, parasitological, serologic, and genomic data. Relevant methodologies include mechanistic