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, the scattering geometry can be reconstructed mathematically (this is called inverse scattering). This requires both sophisticated mathematical models and efficiently implemented algorithms. In the case of wafer
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knowledge acquisition (machine learning), the complexity of learning algorithms, pattern recognition with artificial neural networks, computational geometry and information processing in biological neural
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12 Sep 2025 Job Information Organisation/Company CNRS Department Laboratoire d'Informatique, Signaux et Systèmes de Sophia Antipolis Research Field Engineering Computer science Mathematics
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Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The PhD positions Press forming of thermoplastic composites Press forming is
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well as to optimize the tooling geometry. These process simulations require efficient numerical algorithms to be practical and to enable robust optimization. Therefore, in this project you will: Develop efficient
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interest in expanding their knowledge in both domains. (1) Geometry/Topology -related methods in computer science. (2) Machine Learning. (For example, graph neural networks, generative networks, or neural
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windows as well as to optimize the tooling geometry. These process simulations require efficient numerical algorithms to be practical and to enable robust optimization. Therefore, in this project you will
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measurements are sensitive to the dielectric constant and object geometry. So far, we have used this technology to estimate the vegetation water content (VWC), provide information on the vegetation structure
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on the theoretical and algorithmic development of control methods that combine physical modeling and real-time computation. The work will involve deriving reduced-order models, designing controllers that exploit
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nature. The PhD candidate will focus on the theoretical and algorithmic development of control methods that combine physical modeling and real-time computation. The work will involve deriving reduced-order