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collaboration with other CEA teams, notably ; * Parallel and cluster computing environment and efficient LP/MILP algorithms for our large-scale models ; * Data structuring and storage solutions for model input
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Proficiency in numerical methods and programming Prior knowledges to Rydberg‑atom experiments, RF field sensing, or related quantum‑sensor technologies will be advantageous We offer: An internship in the heart
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serve as the foundation for advanced AI/ML-based classification methods, opening the door to robust and efficient object recognition capabilities. Moyens / Méthodes / Logiciels State of the art of
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long repetitive and complex process. (2) Assess how LLM perform and can be complementary to traditional tools used for evaluation (formal methods, using Frama-C and Lazart). Internship tasks •Literature
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programming based global energy system models (ate different geographical scales), based on the TIMES modelling framework. You bring your knowledge of quantitative methods and economic analysis, in some of the
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their reliability for nuclear safety applications. Methods / Means Density Functional Theory (VASP), Classical molecular dynamics (LAMMPS), ML interatomic potentials Applicant Profile We are seeking for a Master’s
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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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efficiency exceeding 15%, based on GaN technology. Methods / Means Analytical, Matlab, ADS, Python Applicant Profile You are working toward a master of research or engineering degree in electrical engineering
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on efficiency in surface, power consumption, and computing performance. Vision Transformers (ViTs) have recently demonstrated superior performance over Convolutional Neural Networks (CNNs) in a wide