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Field
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Postdoctoral Fellowship in AI and Large Language Models for Transforming Pediatric Healthcare The Computational Health Informatics Program (CHIP) at Boston Children's Hospital, affiliated with
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, leveraging large datasets. Position Description: A typical empirical project involves refining a research question, designing an experiment or survey, analyzing historical and experimental data, and writing
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with the PIs and autonomously, and will be proficient in advanced econometric techniques, leveraging large datasets. Position Description: A typical empirical project involves refining a research
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associate to work with Professor Christopher Kuzawa at Harvard University. The postdoc will oversee analysis and write up of an extensive longitudinal dataset that has followed a large population in Cebu
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one or more of the following: working with large-scale hydrologic models, high-performance and cloud computing, programming in Python, data analysis and visualization, geospatial analysis, and
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biased narratives in public discourse sustain intergroup conflict and inequality? How do large-scale upheavals shape our collective identities and narratives? More information is available here . We
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computational colleagues to build, train, and evaluate cutting edge AI models using large proprietary oncology datasets Leverage multimodal high dimensional data to investigate relationship between heterogeneous
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biology, biophysics, computer science, engineering, mathematical physics, or related disciplines. Reporting to Research Scientists, Data Scientists or the Center Director, as appropriate, Fellows
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experimental expertise and competent research groups. All principal investigators collaborate closely with the aspiration of realizing large-scale practical quantum computing devices through the development
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large AI models or their applications. Current PLI projects involve work with language, images, multimodal data, science/math, code, and scientific data. PLI is also focused on AI safety, fairness, and