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, with a particular affinity for geometric and model-based approaches to 3D understanding, is considered an asset. You have a proactive and independent working attitude. You can report clearly, both orally
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Institut National des Sciences Appliquées de Lyon | Villeurbanne, Rhone Alpes | France | 23 minutes ago
solutions for vibration and noise control in lightweight structures (https://cordis.europa.eu/project/id/101227712 ). The project focuses on the development of Acoustic Black Hole (ABH) technologies
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techniques. Geometric frustration in quantum systems leads to a tight competition between qualitatively new collective spin states, such as topological structures, quantum spin liquids, multipolar ordered
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of manufactured parts, particularly in terms of geometrical accuracy, microstructural control, and mechanical performance. This PhD project aims to develop a Multiphysics model and simulation to gain in-depth
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software protocol capable of generating a three-dimensional multispectral model augmented with nuclear measurement data and deployed in a form suitable for remote inspection and AR/VR-supported training
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) matrix architecture are influenced by the mechanical and geometric properties of their environment. These computational models can provide crucial mechanistic insights into the key parameters governing
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? We urgently need breakthrough research in: recyclable & durable materials fast, data-driven surrogate models lifecycle-conscious design to reduce costs, increase reliability, and accelerate the North
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, or geometric deep learning. Experience with optimization methods, numerical modeling, or simulation of complex systems. Experience with 3D modeling, CAD APIs, or computational geometry is an advantage
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, public authorities in their decisions and businesses in their strategies. Do you want to know more about LIST? Check our website: https://www.list.lu/ How will you contribute? You will develop a multi
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, artificial intelligence, and its applications to large scale data domains in science and industry. This includes the development of deep generative models, methods for approximate inference, probabilistic