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initiatives, the French Mineral Resources Inventory, and European research projects on new quantum gravimetric sensors. In these projects, as well as in future initiatives, you will be involved from
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minimizing error and maximizing efficiency, is computationally challenging—no known polynomial-time algorithm exists to solve it optimally in all cases. Because of this complexity, researchers typically rely
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(formulation, algorithms, applications in structural mechanics), HPC computing, reduced-order modelling, machine learning, Vibrations and structural dynamics, architected materials, Additive manufacturing
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interdisciplinary, and together we contribute to science and society. Your role Multi-omics data integration and workflow improvement Development and application of machine learning-based algorithms
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) — to join our team. You will be directly involved in developing and optimizing ion beam processes to improve device performance in MRAM and magnetic sensor applications. Beyond R&D, we are looking for a
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topological textures. A wide range of applied functionalities could be considered: terahertz sources, unconventional computing and AI, security components, telecommunications, sensors, memories etc.
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candidates may be asked to teach: Introductory programming classes Core undergraduate CS classes such as: Human Computer Interaction, Database Applications, Algorithms and Data Structures, Software engineering
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techniques and the structure of bilevel problems in large-scale settings. Objectives The goal of this postdoctoral project is to develop scalable blackbox optimization algorithms tailored to bilevel problems
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combining multiple ML models have been explored to optimise predictions, enabling algorithms to collaborate and achieve better results. Ensemble methods, in particular, have demonstrated superior performance
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to accelerate evaluation of costly simulations Genetic algorithms and other evolutionary techniques to generate a diverse set of high-performing solutions. You will design and implement new optimization