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solutions that maximize operational efficiency, minimize network impacts, and ensure the long-term sustainability of the proposed approaches. The project investigates optimized EV charging strategies aligned
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of the optical localization system for mobile robots in dynamic and unstructured environments. Main activities • Development of an optical localization method for mobile robots operating in indoor and/or outdoor
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-tuning, multimodality, MLOps, and model management. Ability to optimize AI models under energy and memory constraints. Experience applying AI across diverse domains (health, mobility, cybersecurity, energy
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• Ability to work within a French research environment • Experience in optimizing protocols or developing new protocols • Proficiency with approaches and experimental design for mesocosm studies
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techniques for biological tissue studies. The candidate will work is this research team. The PhD candidate will present his work in international conferences around the world (1 to 3 international trips
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MSc in applied mathematics or engineering Strong analytical and numerical skills Knowledge of optimization and operations management Knowledge of programming, possibly Python Preferred knowledge
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: For applications requiring short packets / low latency, it is important to obtain tight bounds for the optimal secrecy rate in finite blocklength. Building on the theoretical breakthrough by Polyanskiy