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our community. We are now looking for a Doctoral Researcher in AI and Quantum-Inspired Optimization for Sustainable Energy Systems Are you passionate about developing AI-based and quantum-inspired
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techno-economic analysis, life-cycle assessment, mathematical optimization, process-oriented modeling of industrial energy systems, and the analysis of regulatory frameworks. In particular, we focus on
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Recommendation letter(s) The selected candidate is expected to join the lab early in 2027 (depending on visa process). Website for additional job details https://6gmobile.fel.cvut.cz/open-positions
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together: https://uclouvain.be/fr/emploi/politique-personnel.html Post description Within the Louvain School of Management (LSM) and the Louvain Institute of Data Analysis and Modeling in economics and
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/Optimization research group within the Department of Mathematics. The successful candidate is expected to establish a research and teaching focus in optimization. The Department is looking for a
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backbone of tomorrow's Power-to-X plants. This 3-year PhD position offers a unique opportunity to build a research career at the intersection of digital twins, multi-timescale optimization, and
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Inria, the French national research institute for the digital sciences | Gif-sur-Yvette, Île-de-France | France | 12 days ago
activities Access to vocational training Gratification Selection process Website for additional job details https://jobs.inria.fr/public/classic/en/offres/2026-10564 Work Location(s) Number of offers
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optimization of communications, security, and computation in resource-constrained architectures with an emphasis on semantic and context aware communications. The post concerns the study of semantic
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University of North Carolina at Chapel Hill | North Wilkesboro, North Carolina | United States | about 16 hours ago
intelligence or a related field. This early career hire will focus on foundational statistical and optimization methods for safe and reliable AI, with applications in biomedicine and public health. Areas
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enabling process monitoring, learning, and policy training while ensuring safety and efficiency. For this, we develop novel learning-based control methods with practical applicability and theoretical