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and in other collaborating labs at Stanford to tackle emerging clinical questions in oncology, utilizing various AI methods, predictive modeling approaches, and large language models. Specific areas
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data as requested by principal investigator or supervisor; use common statistical programs requiring the application of job control language in generating and organizing data. * Adapt new, nonstandard
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HAI Postdoctoral Fellowship with Professor Chris Potts, Department of Linguistics Foundation Models (FMs) are enabling researchers to build AI systems at higher levels of abstraction and with lower
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principal investigator or supervisor; use common statistical programs requiring the application of job control language in generating and organizing data. • Adapt new, nonstandard methods outlined by
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the supervisor outlines conceptual approach. ● Build and organize data as requested by principal investigator or supervisor; use common statistical programs requiring the application of job control language in
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viruses 4. Integrating AI tools like large language models to curate antiviral drug resistance papers and to manage inquiries This fellowship is designed to hone your skills and foster new learning. You’ll
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the microbiota). These interactions are crucial for promoting our health but also can lead to many inflammatory diseases. We seek to understand the complex molecular language that governs these host-microbiota
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organize data as requested by principal investigator or supervisor; use common statistical programs requiring the application of job control language in generating and organizing data. Adapt new
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of Medicine at Stanford University. The aim of the post-doc is to study how innovations in AI, especially adaptation of Large Language Models (LLMs) architectures for time-series data, can be used in study of
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communication and collaboration with humans. This project will comprise two highly related aims. The first component of this project will entail developing grounded, joint vision and language-understanding