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réseaux neuronaux) et les décompositions tensorielles (multicouches) de rang faible [5,6,7], qui fournissent un cadre mathématique rigoureux pour développer des nouveaux algorithmes et architectures et pour
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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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Interatomic Potentials) code for ternary compounds with variable composition with crystal structure optimization algorithms (evolutionary, random, etc.); - Application of the CSP DFT/MLIP methodology to various
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to process the quantity of experiments conducted with one or more fish swimming simultaneously, on the one hand; and on the other hand, to implement a data fusion algorithm to improve the overall precision
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with signal processing and control algorithms. Excellent communication skills in English (written and spoken); ability to work in interdisciplinary teams and to publish scientific results. A strong
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-luminosity phase of the LHC. The successful candidate will work in close collaboration with other members of the Particle Physics team, and with members of the Computing, Algorithms and Data team at L2IT
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order model, machine learning, data-driven algorithms, deep reinforcement learning The Pprime laboratory is a CNRS Research Unit. Its scientific activity covers a wide spectrum from materials physics
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Inria, the French national research institute for the digital sciences | Paris 15, le de France | France | 3 months ago
distributed optimization with noisy communication channels, accurately study the selected algorithms, participate in the development and maintenance of the PEPit (https://pepit.readthedocs.io/ ) software
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Inria, the French national research institute for the digital sciences | Saint Martin, Midi Pyrenees | France | about 2 months ago
follows a phased algorithm: 1) generate an initial training set by uniformly sampling input points 2) (re)train the model on the trainng set 3) use feedback from the model’s performance to generate/augment
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knowledge of multi-objective problems. Master students or Engineers in the field of Process Systems Engineering are strongly encouraged to apply. Knowledge of machine learning algorithms, energy markets and