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resources to carry out your assignments. YOUR ASSIGNMENTS: The internship will develop and implement scalable, high‑performance algorithms for transient Lindblad dynamics tailored to the multi‑level Rydberg
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the heart of the Grenoble metropolitan area, easily accessible via the CEA's soft mobility program. A unique research environment dedicated to topics with high societal impact. Experience in a cutting-edge
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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
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of this internship is to develop wideband or dual-band matching networks and power combiners using an analytical approach that enables the direct synthesis of these components from specified performance requirements
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Stage - Generative Privacy Attacks and Defenses in Federated Learning via Diffusion Models H/F This internship focuses on exploring the dual role of diffusion models in Federated Learning: understanding how they can be used to reconstruct sensitive client data and designing robust defense...