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Research Areas: mechanical, fluid transport, photonic, and energy materials, supported by four Cross Areas dedicated to imaging, modeling, data, and exploitation. Together, they form a vibrant
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models, and the co-design, execution, and data analysis of observation programs to evaluate models and the effectiveness of interventions. Communication of results to both the science community, and the
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they change through time. To translate eBird observations into robust data products we create custom modeling workflows designed to fill spatiotemporal gaps based on remote sensing data while controlling
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Boston University Chobanian & Avedisian School of Medicine | Boston, Massachusetts | United States | about 7 hours ago
will begin immediately and continues until the post is filled. Application Materials Required: Further Info: https://www.bumc.bu.edu/busm-pm/ Boston University Chobanian & Avedisian School of Medicine
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student success by creating an optimum learning environment, responding to student needs, managing effective instructional activities, modeling employability skills, demonstrating professionalism
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, noise and vibrations. When they occur near surfaces and with sufficient intensity, they can damage materials, leading to a gradual loss of material, known as cavitation erosion. To date, there is no fully
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materials, devices, and manufacturing. More than 1 year of experience working in a business development role at a company with a focus on software, AI, semiconductor, large language model or machine-learning
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virology, hostvirus interactions, and mechanisms of viral pathogenesis. This position requires technical expertise in molecular biology, cell culture, and animal models, as well as strong organizational and
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: 88136BR Supervises staff involved in providing clinical patient care. Assists in ensuring the quality of patient care delivery in a specific patient care area and serves as a role model for professional
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pipelines that push technological boundaries for our clients. The Engineer will tackle complex challenges at the intersection of Large Language Models, Computer Vision, and Predictive Analytics while ensuring