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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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-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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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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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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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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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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of machine learning algorithms are of real interest in improving the accuracy of water quality measurements, particularly in identifying, accounting for, and neutralizing ionic interference. The second key
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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
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) for the high-luminosity phase of the LHC, in particular on its mechanical design, on the generation of the L1 trigger primitives, and on the development of offline reconstruction algorithms. In addition, it is