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: understanding how they can be used to reconstruct sensitive client data and designing robust defense mechanisms to protect against such threats. Context Federated Learning (FL) enables multiple clients
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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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, which performs numerical analytics during the simulation. This is necessary due to the ever-growing gap between file system bandwidth and compute capacities. To this end, we are developing the Deisa
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or embedded systems. You have experience in computer architecture and/or hardware synthesis and/or formal methods for hardware verification. You enjoy working in an applied research environment at the state
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responsible to develop and test the new software in collaboration with experts of genomics at Joliot and of computer science at MdS. Your mission will include: Discussions and set-up of the physical models
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We are looking for a candidate with a Master's degree, Engineer's degree or PhD in computer science, junior or senior, to join a team responsible for the packaging, deployment, and testing