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external) is reimagining the experimental neuroscience pipeline with big data and AI at its core. A central goal of the project is to build a foundation model of the visual brain—a “digital twin” that
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will drive research on clinician–AI and patient–AI interaction, focusing on how systems such as LLM-based tools, decision support systems, and adaptive health technologies are integrated into clinical
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or lead mixed-methods analysis combining survey data with qualitative findings where applicable. Reporting & Dissemination Develop data visualizations, technical reports, donor updates, and academic
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internal equity. Pay Range: 76,383-86,383 Our lab investigates the functional principles, development, and computational properties of organism-wide circuits for brain-body interactions. We
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, econometrics/causal inference, data management, coding (e.g., in Stata or R), and applied policy-relevant research. Skills in geospatial analysis and/or data visualization would be a plus. The candidate should
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Chemically Induced Protein Interactions. Accounts of Chemical Research. https://doi.org/10.1021/acs.accounts.5c00225 (link is external) Specific postdoctoral projects may include: Reconstitution and cryo-EM
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and early-onset cases without a known genetic cause. We are also interested in genetic interactions (epistasis), tandem repeats, machine learning, and other areas of AD research that have not yet been
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therapeutically target the molecular mechanisms that underlie neuronal interactions with gliomas (Venkatesh et al, 2017, Nature). In addition to these studies of mature neurons in the glioma microenvironment, we
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internal equity. Pay Range: 76,383-86,383 Our lab investigates the functional principles, development, and computational properties of organism-wide circuits for brain-body interactions. We
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interactions with other gaseous pollutants from gas stoves and home appliances. The studies will build upon Stanford medical expertise with unique capabilities to quantify UFPM and other pollutants in hundreds