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it; as well as have theoretical skills including algorithm implementation/development and data visualization. Experience and interests include designing machine learning pipelines, building web
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for this position include a PhD in Computer Science, Artificial Intelligence, Natural Language Processing, Human-Computer Interaction, or a closely related field. Candidates should have demonstrated expertise in
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large-scale optimization and theoretical combinatorial optimization, algorithmic reasoning remains a significant challenge for artificial intelligence. Our lab’s research is driven by the observation
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an ambitious and motivated postdoctoral scholar to join an exciting project focused on a unique alignment of visual, acoustic, and structural data for a radical new assessment of anthropogenic impact on our
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making systems. This project will be under the mentorship of Professor Mykel Kochenderfer in the Stanford Intelligent Systems Lab. The postdoc will define promising research directions for extending AST
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understanding of neuroscience but also advanced technical expertise in machine learning, artificial intelligence, and data modeling approaches. Responsibilities: Conduct research on the mechanisms underlying
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patients and established pipelines for data pre-processing, analysis, and integration (Good et al. Nat Med 2022; In Preparation). We now seek to build generative artificial intelligence (AI) models
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communicate by flexibly reasoning about what other agents know and want. Recently, we have been exploring how this framework of inferential social learning can be applied to develop socially intelligent
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Health Platform, advancing interdisciplinary research at the intersection of artificial intelligence, bioinformatics, and equity in Asian health research. Various projects may include: Contribute
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disparities in care. Methods include artificial intelligence approaches for analyzing electronic health records data, quality improvement methodology, engagement of and collaboration with community stakeholders