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the final phase, the study focuses on the advanced optimization of the composite by integrating functional nanostructures, particularly carbon nanotubes (CNTs). Due to their nanoscale cylindrical structure
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dry-lab scientists in experimental design and sample collection for optimal analyses. Presentation of the progress of the project to team members. Attendance to international conferences for data
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Laboratoire National de Métrologie et d'Essais - LNE | Paris 15, le de France | France | 14 days ago
reference data generation here is to state the optimality conditions for the considered mathematical formulation and then derive datasets that perfectly meet these conditions. To investigate and develop
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digital tools for the design and optimization of sustainable agroecological orchards, integrating environmental constraints and enabling the exploration of innovative strategies for varietal selection and
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, economic, or social constraints. Heudiasyc's research is organized into three specialized teams: CID: Knowledge, Uncertainty, Data SCOP: Reliability, Communication, Optimization SyRI: Robotic Systems in
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. Personalized Federated Diffusion with Privacy Guarantees. 2025. [8] Fang et al. GIFD: A Generative Gradient Inversion Method with Feature Domain Optimization ICCV 2023. [9] Bonawitz et al. Practical Secure
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therapeutic targets 2/ Leveraging the digital revolution by optimizing the analysis of available patient data through artificial intelligence and new connected devices ; 3/ Encouraging transdisciplinary
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Inria, the French national research institute for the digital sciences | Pau, Aquitaine | France | 8 days ago
dispersion, crucial for high-frequency content in FWI. HPC readiness: The solver design will be optimized for modern heterogeneous clusters (CPU/GPU). Innovation opportunity: Potential integration into next
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), drives technology transfer and innovation in embedded systems. The Embedded Artificial Intelligence Laboratory (LIAE) specializes in designing optimized AI solutions for embedded environments, with a focus
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the context of LOFAR 2.0 (Harish Vedantham et al., ASTRON, Netherlands), MeerKAT, and SKA (Oleg Smirnov et al., SARAO, South Africa). It is funded by LIRA, which also provides optimal support to its doctoral