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multimodal MRI data from children with NF1 using the Siemens Cima X scanner at Stanford’s Lucas Center for Imaging. The position sits at the intersection of advanced neuroimaging methods, longitudinal clinical
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of translational neuroscience, clinical phenotyping, and advanced neuroimaging methodologies. Neuropsychological data will be integrated with multimodal imaging findings and basic science investigations to elucidate
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into the brain's algorithms of perception and cognition while serving as a key resource for aligning artificial intelligence models with human-like neural representations. As part of this project, we are seeking
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-scale multimodal datasets and collaborating with leading experts in spatial biology, AI, and cancer research. Responsibilities: Design and train state-of-the-art generative AI architectures (e.g
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for action ("affordances") shape neural representations, perception, and behavior. Why this position? You will sit at the center of a uniquely cross‑disciplinary team and work closely a network of
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community wellbeing. One project evaluates the impacts of urban civilian safety practitioners using AI-driven multimodal sensing to understand mechanisms of de-escalation and disorder reduction in San