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solutions. Through interdisciplinary programmes, living labs and large-scale testbeds, ERI@N drives impactful translational R&D with strong industry deployment. More details: https://www.ntu.edu.sg/erian We
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team. In this role, the engineer will work with the research team of Professor James Tour in the Department of Chemistry. The candidate will contribute to the design, testing, and optimization
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North Carolina A&T State University | Greensboro, North Carolina | United States | about 8 hours ago
ingredients on human health outcomes. This includes designing, executing, and optimizing in vitro cell culture and microbiological experiments relevant to gut microbiome function, diabetes, lipid dysbiosis, and
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 1 day ago
-criteria evaluation and identification of optimal retrofit strategies. The scholarship holder will therefore work within the scope of assessing the energy performance and environmental impact of existing
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production vendors) to modernize systems and optimize performance. Required Qualifications: Bachelor's degree in Marketing, Communications, Business, or related field. Minimum of 5 years of experience in media
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of Applied Mathematics and Statistics at the Department of Mathematical Sciences. Under the supervision of Malin Rau, you will contribute to impactful research in optimization. About us The department of
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to ensure optimal systems for efficiency, compliance, safety, financial oversight, and contractual expertise in negotiations and execution, as well as create and implement quality improvement processes
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thin films. Technical difficulties remain however for the realization of optimal epitaxial layers, in accordance with this new approach and able to withstand a voltage of 1400 V. The proposed thesis will
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the ability to prioritize incidents based on business impact. Performance Optimization: Knowledge of techniques to optimize AI system and data pipeline performance, including resource allocation, scaling
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examines how digital twins, simulation-based multi-objective optimization, and AI-driven decision support systems can enable manufacturing industries to maintain stable production, optimize energy usage, and