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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 4 days ago
research. We foster programs in the areas of basic, translational, mechanistic and population research. Position Summary The NC Statewide Program for Infection Control and Epidemiology (SPICE) promotes
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network of over 15 libraries with over 400 employees. We are committed to fueling the teaching, learning and research across Stanford by acquiring, stewarding, and making available a robust collection
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broader community. We take pride in delivering exceptional service, sharing our expertise, and upholding the highest standards to ensure a world-class campus experience. Please visit us at: https
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interpretability, robustness, and efficiency. Contribute to the team's engineering culture by introducing and maintaining quality standards including automated testing, version-controlled releases, and scalable
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, hands-on CEO to lead ExoDetect through its next phase: transforming a validated prototype into a robust, manufacturable, and commercially viable diagnostic product. This is a high-impact, execution
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capital budgets. Through strong governance, robust financial processes, and cutting-edge systems, we ensure every dollar is put to its best use, fueling research, education, and transformation. Why Join Us
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data, integrating multiple data sources, and supporting analytical modelling that informs infrastructure planning and policy. The position emphasises robust data engineering practices, reproducible
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to lead the end-to-end transformation of our testing strategy, processes, and tooling for Clinical Trial Database systems and API integrations. This role will drive improvements in efficiency, robustness
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components, and the computer-controlled systems that support plant operations. Additional Information: This is a full-time (100% FTE), permanent position. This position is overtime eligible. Monthly Salary
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Institut de Recherche en Génie Civil et Mécanique (GeM) | Saint Nazaire, Pays de la Loire | France | about 1 month ago
ou encore de propager les incertitudes au travers du modèle afin de rendre plus robuste les différentes prédictions. Les mesures seront éventuellement comparées à d’autres techniques de caractérisation