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of lattice CAD models via generative/parametric design (e.g., Grasshopper); - Numerical FE simulation of meta-grains (Abaqus or Z-Set); - Extraction of key data (mechanical properties, critical load
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of Multiple Forest Risks in Nouvelle- Aquitaine), which includes this work on zombie fires. 2. Research focus and methodology The research project focuses on the experimental and numerical study of "underground
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schemes for their discretization Knowledge of numerical optimization Knowledge of Python, Matlab and FOTRAN90 compiled code, use of high-performance parallel computing servers Ability to synthesize and
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Ecole Nationale Supérieure des Mines de Saint Etienne | Saint Etienne, Rhone Alpes | France | 2 months ago
the ICM program. The teachings should focus on optimization, operational research, industrial statistics, numerical methods, or multicriteria analysis, as well as other programs. - Research : Conduct high
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will be based on numerical optimization approaches and machine learning techniques. The different tools developed are based on data, such as load curves, which are often totally or partially missing
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Inria, the French national research institute for the digital sciences | Talence, Aquitaine | France | about 2 months ago
and numerical constrained optimization. The recruited person will have the opportunity to benefit from exchanges with these people but will also be working closely with: Vincent Padois, PI
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Inria, the French national research institute for the digital sciences | Talence, Aquitaine | France | 2 months ago
approximately composed of 15 people whose core expertise ranges from robotics to cognitive sciences including biomechanics and numerical constrained optimization. The recruited person will have the opportunity
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computational fluid mechanics models [9]. This project aims to address this fundamental research gap, combining state-of-the-art laser diagnostics with carefully designed laminar and turbulent burners optimized
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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
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(Yaghmaie et al. 2019) based on reinforcement learning technique, with specific activation functions, the authors show that there could be solutions to optimization problems under constraints for a class of