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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 1 month ago
, molecular engineers, and electrochemists. The long-term goal of the work is to advance robust, scalable, and commercially translatable biosensor technologies. The candidate will collaborate with academic
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. Duke aspires to create a community built on collaboration, innovation, creativity, and belonging. Our collective success depends on the robust exchange of ideas-an exchange that is best when the rich
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results in a robust biological context Ensure reproducibility, data management, and documentation of computational workflows in high-performance computing environments Collaborate closely with experts in
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university system based exclusively in the robust Dallas-Fort Worth region. We are growing with the North Texas region, employing more than 14,000 employees, educating a record 49,000+ students across our
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collaboration, innovation, creativity, and belonging. Our collective success depends on the robust exchange of ideas-an exchange that is best when the rich diversity of our perspectives, backgrounds, and
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small-scale models via distillation from larger models, including through the use of synthetic data. This in turn raises interesting questions about the robustness of the resulting models, their ability
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Job description The Challenge As process industries transition to circular models, companies within Hubs for Circularity (H4C) need robust tools to navigate the financial complexities of industrial
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. The role is designed to strengthen research capacity in empirical, data-driven analysis with a particular focus on generating robust evidence that challenges prevailing assumptions and dominant narratives
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robust educational and research environments that leave an impact regionally, nationally, and internationally. Our vision is "Stronger together – we build the university through interdisciplinary
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prototyping and on-sky testing perform detailed laboratory characterisation of astrophotonic components, including designing robust experimental procedures and analysis of data contribute to novel data analysis