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and deep learning methods for large-scale genomic, clinical, and imaging biobank data, with stable multi-year NIH support. The Zhi Laboratory has a sustained track record of methods development
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-scale human datasets. You will: - Build and apply machine learning and deep learning models to multi-scale (cells, brains, patients), multi-modal (omics, biosensor data, vision, electronic health data
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student, (d) to learn literature review, critical thinking, and scientific methods, (e) to develop deep and broad knowledge in HIV virology and immunology, (f) to develop responsible conduct in wet-lab
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modeling of novel radiopharmaceuticals, development of advanced image reconstruction algorithms for quantitative PET and PET/MR imaging and the development of deep learning methods to improve quantitative
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. 5. Deep intellectual curiosity and genuine enthusiasm for scholarship, research, and higher education; the capacity to engage thoughtfully with complex academic priorities and translate them
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research career. Research and technical training Training will include hands-on work in the following areas: Developing and validating deep-learning and machine-learning models using echocardiography
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. Required Skills & Abilities: 1. Strong strategic leadership and organizational management skills. 2. Deep understanding of fundraising and alumni engagement practices. 3. Excellent communication and
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, the Peabody Museum, or more technical parts of the University for periods of time to learn about both research and operational workflows. Connections with the Wu Tsai Institute, the AI at Yale program, the Data
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gatherings to amplify the findings and foster new conservation partnerships. Required Skills and Abilities 1. Deep, demonstrated understanding of federal-tribal relations, tribal jurisdiction, and Indigenous
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+ years of relevant experience; a deep understanding of economics and social policy; experience communicating quantitative research is strongly desired. Although this position is primarily remote, a minimum