22 machine-learning "https:" "https:" "https:" Postdoctoral positions at Stanford University in United States
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large‑scale systems neuroscience with machine learning to derive principled models of cortical computation. Our newly refurbished primate facility, state‑of‑the‑art Neuropixels rigs, and high
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cyclones, the Madden–Julian Oscillation, and atmospheric rivers. We combine theory, observations, a hierarchy of numerical models, and machine-learning methods to understand their formation, dynamics
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technical expertise in machine learning, artificial intelligence, and data modeling approaches. We are committed to investigating the mechanisms of brain aging and developing innovative interventions to
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cardiac surgery outcomes research and predictive analytics using advanced statistical and machine learning methods applied to large claims and electronic health record databases and multimodal data
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density in regulating these processes. The insights gained from these empirical studies will be paired with computational biology and machine learning to develop predictive AI models of how cells
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, machine learning, computer science, statistics, engineering, medicine, or a related field. Strong candidates may have experience with large-scale human datasets, machine learning, statistical genetics
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processing tools, including fMRI, structural MRI, diffusion MRI, EEG, or related modalities. Strong publication record in AI, machine learning, computational neuroscience, or neuroscience venues, such as
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. Developing the research program will include supporting the team with quantitative, inferential and spatial analysis, as well as integrating machine learning techniques, and leading and drafting manuscripts
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, leveraging a novel in-vitro model of the human uterus and/or cutting edges machine learning techniques to make foundational discoveries in reproductive medicine. The annual salary for this full-time position
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motivated postdoctoral researcher with: Experience in relational databases, big data curation and analysis Expertise in machine learning, including building and deploying prediction models Strong data