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architecture beyond the CMOS-based scheme and suitable energy-efficient hardware for the unconventional scheme is highly desired for future highly-integrated AI hardware on a chip. The French team at IEMN has
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theoretical and experimental tools to control the magnon dissipation rate using feedback protocols, thereby enabling the continued development, deployment, and use of quantum computing hardware, in alignment
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engineers (technical staff) will assist the PostDoc for all what concerns hardware/software development and maintenance of the robotic platforms. Where to apply Website https://emploi.cnrs.fr/Offres/CDD
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performance of hardware neural networks. • Contribution to neuromorphic demonstrators: You will actively participate in the development of capacitive neuromorphic circuits and in in-memory computing
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. Experimental Validation • Validation in real-time simulation. • Validation on HIL/PHIL (Hardware-in-the-Loop and Power-Hardware-in-the-Loop) platforms. • Performance evaluation on scenarios representative
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the SPIN Doctoral School (ed-spin.doctorat-bretagne.fr). Vincent Lebastard at IMT-Atl Nantes will co-supervised the PhD thesis. This thesis is part of the PEPR Acc Robotique MiniRo (https://anr.fr/fileadmin
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in our fundamental understanding of turbulence. As computing hardware reaches the physical limits of miniaturisation, future advances in high Reynolds number DNS using existing methods can only be