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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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tasks requiring initiative and judgment by applying basic knowledge and understanding of empirical methodologies and models. General instructions provided by the faculty supervisor as needed. May
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by applying basic knowledge and understanding of empirical methodologies and models. General instructions provided by the faculty supervisor as needed. May interpret research results in collaboration
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: Conceptualizing suitable empirical methodologies and models Collecting, managing, and structuring quantitative datasets Conducting statistical analyses of complex datasets and interpreting results Report writing
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empirical methodologies and models Collecting, managing, and structuring quantitative datasets Conducting statistical analyses of complex datasets and interpreting results Report writing and manuscript
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working with large healthcare datasets (EHRs, claims, registries). Proficiency in R or Python. Strong quantitative skills and familiarity with advanced modeling techniques. Excellent written and verbal