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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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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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biological diversity Experience in and/or commitment to working across cultures with non-academic research partners Expertise in spatial analysis in ArcGIS or equivalent Excellent R programming language skills
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agricultural economics, and an understanding of frontier methods in Natural Language Modeling, Large Language Models, and Big Data Management and Analytics. The candidate will be responsible for compiling and
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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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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
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understanding of current AI techniques and approaches including supervised and unsupervised machine learning, symbolic AI, and generative AI (including large language models) [technical understanding of one
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to support deliberate practice for socially important topics. The team aims to use large language models to understand contentious topics and to support civil discourse engagement through human-AI
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. (iii) An existing AI pipeline (Bioinformatics 38:3385, 2022) for analysis of genetic candidates will be optimized by testing whether: recently developed large language models can be used for candidate
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community partners to test and validate these assessments with children from diverse language, racial/ethnic, and socioeconomic backgrounds to ensure that tasks yield information that is equitable and