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an integrated framework for co-design and adaptive operation of electrical networks. DynConGrid develops real-time Model Predictive Control (MPC) for congestion management by reconfiguring topology, curtailing
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 6 days ago
the prediction of vehicle flows, energy demand, and flexibility of electric vehicle fleets, with applications to energy and transportation systems. The work lies at the intersection of systems and control, data
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settings. The ultimate goal is to enable early, systematic, and robust screening of children at risk of neurodevelopmental disorders. Deep learning models typically produce point predictions, whose
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Associate in Research The role involves developing and optimizing machine learning models to predict infectious diseases using multimodal health data. Responsibilities include analyzing correlations between
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drug residence time, creating a high burden for patients and clinics. We thus aim to develop a minimally invasive, injectable biomaterial platform designed to enable predictable, long-term ocular
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. Preferred Qualifications Experience in development of predictive video display systems Experience in teleoperation and/or control of autonomous vehicles Experience in working with sensor systems such as GNSS
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at the University of Rouen Normandie is seeking a motivated PhD candidate for the CRONOSS project, which aims to revolutionize crystallization control by combining in silico simulations with experimental validation
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, implement, and tune advanced control augmentation techniques (e.g., model predictive control, adaptive control) to enhance the stability and agility of COTS drones under dynamic conditions. Swarm Intelligence
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at: https://arxiv . org/abs/2207.06196 [12] Hafner, D., Lillicrap, T., Ba, J., Norouzi, M. (2019). Dream to Control: Learning Behaviors by Latent Imagination. arXiv preprint arXiv:1912.01603. Available
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