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experience with HHG sources are a plus but not critical. Knowledge of programing languages such as Python (and with finite element simulations specifically) would be also valuable.
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microarchitectural vulnerabilities and/or prove the robustness, for a given fault model, of various RISC-V based processors [3]. For instance, we apply this methodology to the OpenTitan secure element and formally
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chemistries and improve the battery performance and lifetime. In the PEPR Batteries OPENSTORM project, synergies are being sought between existing characterization methods to accelerate the study of future
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exploration strategies that go beyond traditional techniques such as linear programming or deterministic solvers. You will work on cutting-edge methods including: Bayesian optimization Surrogate modeling
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potential lends itself to this. Required profile: · With a PhD in physics or mechanical engineering, the successful candidate will have acquired solid skills in the mathematical and numerical methods
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Micha, Research Engineer at CNRS/ESRF, This Post-doctoral position focuses on the development of interpretable artificial intelligence methods for detecting and analysing anomalies in synchrotron beamline
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experiments (experimental economics, preference method, discrete choice method, surveys, etc.), with associated academic publications ? You are familiar with putting forward proposals to help build up
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current methods). One of the long-term objectives will be to conduct a similar study on the human genome (20k genes with 300 to 3M base pairs) on the Exascale machine soon to arrive at CEA. PTC funding is
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between the in-situ data analysis and the numerical simulation. This allows better resource allocations and on-the-fly simulation monitoring. Another aspect that in-situ analysis enables is using AI methods