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École nationale des ponts et chaussées | Champs sur Marne, le de France | France | about 14 hours ago
combining multiple ML models have been explored to optimise predictions, enabling algorithms to collaborate and achieve better results. Ensemble methods, in particular, have demonstrated superior performance
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2 Sep 2025 Job Information Organisation/Company CNRS Department Maison de la Simulation Research Field Computer science Mathematics » Algorithms Researcher Profile Recognised Researcher (R2) Country
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University of Quebec at Rimouski (Canada), the Chrono-Environnement Laboratory (France) and GEODE (France). Within ISEM, He will be under the supervision of Prof. Adam A. Ali and collaborate closely with
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(bacterial, viral, inter-archaeal). - Quantify gene family dynamics (duplication, loss, HGT) by major lineage, and identify evolutionary shifts associated with ecological transitions (thermo/halophily
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control and energy management strategies, including centralized / distributed control approaches, for ESS coordination and ancillary service delivery. Develop optimization algorithms and Al-based methods
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algorithms for optimization Quantum annealing Quantum inspired optimization Quantum machine learning with a special emphasis on classical optimization of QML algorithms Noise mitigation in relation
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interdisciplinary, and together we contribute to science and society. Your role The Developmental and Cellular Biology Group (led by Prof. Jens Schwamborn) at the Luxembourg Centre for Systems Biomedicine utilizes
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Automated Generation of Digital Twins of Fractured Tibial Plateaus for Personalized Surgical plannin
of this project requires the design, development, and training of an artificial intelligence algorithm capable of automatically segmenting the bony structures of both healthy and fractured tibial plateaus
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) For further information about the role, please contact Prof. Dr. Jean-Sébastien Coron, Head of the Department of Computer Science, Email: jean- Your profile A PhD degree in Computer Science or a closely related
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-criteria, defining their formalization as fuzzy subsets, and characterizing their uncertainty; Integrating Machine Learning algorithms to better account for low-level sensor data (precipitation, wind-driven