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, determining their optimal operating points, and integrating them into information processing architectures. The classical approach is to use intensive numerical simulations, but their complexity usually
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: The CAVAA European project (https://cavaa.eu/ ) proposes to realize a theory of awareness instantiated as an integrated computational architecture and its components to explain awareness in biological systems
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have dominated the field in recent years but often suffer from training instabilities. We aim to investigate the interactions between model architectures and data domains in deep learning, focusing
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have developed a new paradigm for controlling micro-photonics systems based on the transition between optical states. We have particularly identified a specific architecture with potential applications
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will join the team "Phagocyte architecture and dynamics" at the IPBS. He/she will develop a research project aiming at understanding the mechanical functioning of phagocytosis. This study will be carried
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"Phagocyte architecture and dynamics" at the IPBS. He/she will develop a research project aiming at understanding the mechanical functioning of phagocytosis. This study will be carried out under
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(Lawrence Livermore National Laboratory), the development of high repetition rate lasers will require the creation of cooled laser chains and the design of architectures to achieve the highest efficiency. In
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input data. The network's architecture itself serves as a prior, enabling the generation of plausible images without the need for extensive training data. Modality-specific considerations (CT, MRI, US
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embarked on emulating Geant4 simulation with generative models, initially GAN and VAE, more recently diffusion model or dedicated hybrid architectures. Current state-of-the-art architectures and open
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Post-doctorate position (M/F) : Exascale Port of a 3D Sparse PIC Simulation Code for Plasma Modeling
to exascale architectures an initial 3D simulation code developed as part of previous work [1]. This work will initially focus on scaling up (distributed memory), optimizing CPU algorithms (vectorization) and