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. The Postdoctoral Scholar will be expected to provide technical leadership in experimental design and measurement, connect experimental observations with gas-phase kinetic and transport models, and communicate
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, observations, a hierarchy of numerical models, and machine-learning methods to understand their formation, dynamics, and predictability. The successful candidate will have substantial freedom to develop
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prognostic markers for psychosis in youth at clinical high risk, using state-of-the-art AI models and multimodal neuroimaging, clinical, and cognitive data. The position will emphasize advanced computational
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modeling, or real-time data analysis. Familiarity with data visualization, reproducible research workflows, version control, and collaborative coding practices. Interest in translating computational methods
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. The ideal candidate will possess not only a deep conceptual understanding of neuroscience but also advanced technical expertise in machine learning, artificial intelligence, and data modeling approaches. We
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of facts makes the study of narcolepsy a simple model and resolving its immunological basis is likely to lead to novel insight into how autoimmunity develops. Finally, narcolepsy is also of great interest
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Brain Foundation Models at Stanford University We are recruiting a highly motivated Postdoctoral Research Fellow to join an interdisciplinary effort at Stanford University focused on building next
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mouse models, in vivo rabbit preparations, and cell culture approaches to study how anesthetics induce unconsciousness and cause toxicity. Our wet bench experiments involve measuring oxygen consumption in
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in human genetics and population data to experimentally testable mechanisms using powerful genetic models. Projects will combine bioinformatics, genomics, genetics, and systems biology, with
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energetic characterization methods (e.g., TGA, DSC, SEM, bomb calorimetry, strand burners). Familiarity with automated experimentation, data acquisition systems, and reactor control. Required Application