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of absorbed light energy effectively converted into mechanical work. In parallel, the influence of the local polymer environment (the “photomorphon”) on photoswitch performance will be investigated using non
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-field code, written in the Cuda C language and parallelized on a single GPU (Graphical Processor Unit). A parallelization on multiple GPUs would be a welcome development during the thesis. Where to apply
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efficiency Optical neuromorphic computing is emerging as a promising alternative to classical electronic architectures, offering advantages in terms of speed, energy consumption, and parallelism. Nonlinear
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of behavioral responses, particularly pain-related outcomes, alongside detailed analysis of tissue inflammation and degeneration. In parallel, cellular studies using human primary cells will provide mechanistic
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massively parallel FFT-based simulation platform for polycrystalline plasticity, enabling efficient simulation of the mechanical response of realistic 3D microstructures. These simulations will be used
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massively parallel FFT-based simulation platform for polycrystalline plasticity, enabling efficient simulation of the mechanical response of realistic 3D microstructures. These simulations will be used
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Inria, the French national research institute for the digital sciences | Palaiseau, le de France | France | 20 days ago
. These simulations are run on highly parallel supercomputers on which both the hardware and the software are optimized for the task at hand. While the computing power of each processing unit is still increasing, the
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. These results will inform on the relevant scaling laws to be used within a parallel experimental research activity carried out within the LOCCO project. This provides an unique opportunity to have a
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details, the following tasks will be carried out in parallel: 1. The PhD student will extend the current database (see, J. Chem. Theory Comput.2025, 21, 8010−8033) by obtaining highly-accurate reference
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, Interactive and Cognitive Systems, Distributed Systems, Parallel Computing, and Networks. The host team, DAISY, is a joint CNRS, Grenoble INP, and UGA research team handling research challenges