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the area of quantum and hybrid classical-quantum networks regarding their design, management, and debugging in distributed architectures. Well-Planned Interdisciplinary Training: To sustainably train PhD
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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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, which is prohibitive for their large-scale deployment. This thesis project aims at proposing new opto-spintronic III-V/Si devices architectures that combine efficiency and low production costs. The OHM
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investigate deep learning architectures capable of learning microstructure-property mappings, including convolutional neural networks for microstructure image analysis, graph-based representations
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that give rotaxanes the ability to produce reactive oxygen species, and applications of these architectures in antibacterial photodynamic therapy. Where to apply Website https://amethis.doctorat.org/amethis
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being reachable within an hour train ride). Website: https://www.iemn.fr/la-recherche/les-groupes/physique/nanostructures-qu… In the digital age, the energy consumption of microelectronic devices presents
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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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investigate deep learning architectures capable of learning microstructure-property mappings, including convolutional neural networks for microstructure image analysis, graph-based representations
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3D environments. • Design of a robust control architecture to ensure autonomous navigation using information from the optical localization system (development of estimation algorithms, use of observers
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LevelPhD or equivalent Skills/Qualifications - Excellent knowledge in architecture of quantized and pruned neural networks - Solid programming skills, languages C / C++ / Python - Solid knowledge in