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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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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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, 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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science, computer science, health or environmental sciences, or environmental economics Experience with causal inference methods, especially fixed-effects regression A demonstrated interest in
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Childhood. (link is external) The program is designed to train fellows to conduct work that is equity-focused—centering systemic equity as an outcome interdisciplinary—examining individual development in
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meet people’s energy needs. Evidence of the health effects of ultrafine particulate matter (UFPM) are growing. The Stanford Medical School (the Luby lab (link is external) ), Doerr School
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features. Using our recently developed chromosome engineering approach, we have created isogenic stem cell lines that allow us to precisely isolate the effects of the chromosomal abnormality from other
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us to precisely isolate the effects of the chromosomal abnormality from other genetic variation (Lee et al., bioRxiv 2025). This project will expand on this work by generating additional patient
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research and work in a collaborative environment. Demonstrated effectiveness in written and oral communication, and the ability to synthesize complex technical and scientific information. Required
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to apply. Basic to advanced experience with computational analysis and R/Python. Excellent oral and written communication skills and be able to work effectively with collaborating researchers. Successful