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efficiency Optical neuromorphic computing is emerging as a promising alternative to classical electronic architectures, offering advantages in terms of speed, energy consumption, and parallelism. Nonlinear
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thermodynamic cycles by combining two complementary approaches: - Generative models derived from artificial intelligence, capable of proposing new process architectures; - Superstructure-based optimization
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congested architectures. For more information, visit my professional website: https://iscr.univ-rennes.fr/daniel-muller Where to apply Website https://emploi.cnrs.fr/Offres/Doctorant/UMR6226-DANMUL-005
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focus on the synthesis and self-assembly of bio-based glycopolymers with comb-like architectures for the design of colored structural materials. These copolymers exhibit interesting properties due
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, real systems must account for losses, non-uniform flux distributions, material limitations, and experimental constraints. Developing realistic cavity architectures and validating them experimentally is
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a major challenge, accounting for up to 50% of global electricity consumption by 2030. This situation is largely due to the Von Neumann computing architecture, which limits the energy efficiency
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-compatible measurement system using a coplanar waveguide architecture, assess their sensitivities, evaluate the possibilities of combining them, and test them with real biological samples—going beyond simple
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excavation of an Abbasid-period archaeological site with a multidisciplinary team ; - Undertake the architectural study of the remains uncovered during the excavation work ; - Carry out the recording and study
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) - employing causal and counterfactual analysis methods to identify the information captured by neural networks, by modifying their architecture and/or representations. - working closely with field linguists
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Contributions - A formal framework for modeling well-being in adaptive learning - A well-being-aware student simulation model - A multi-objective RL framework - An orchestration architecture - Experimental