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focused on advanced structural integrity, intelligent diagnostics, and predictive maintenance of engineering systems. The Mechanics of Intelligent Structures Department operates at the interface
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Research FieldEngineering » Thermal engineeringEducation LevelPhD or equivalent Skills/Qualifications • A PhD degree in technical sciences, specializing in mechanical engineering (PhD Eng.). • Documented
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separation mechanisms, among others.3 The interest in these supramolecular assemblies lies in their sensitivity to environmental conditions, allowing control over the formed structures based
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16 Apr 2026 Job Information Organisation/Company Czech Technical University in Prague Department Department of Physics Research Field Physics » Quantum mechanics Researcher Profile First Stage
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. Environment: PhD student will be working at CEA in Grenoble, a major French National Lab focused on the development of low-carbon energies, and more specifically in IRIG/SYMMES lab (https://www.symmes.fr/en
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transplantation. PhD candidates are employed by university and work in an international research environment with personalized supervision and structured doctoral training, including courses, seminars, and journal
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offers a unique and stimulating scientific environment, structured around team meetings, laboratory seminars, and interdisciplinary public seminars focused on energy and transition-related topics. The PhD
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Laboratoire Interdisciplinaire des Energies de Demain - Université Paris Cité | Paris 15, le de France | France | 18 days ago
the photoinduced strain is transmitted to the surrounding material through photochrome/polymer interactions. To this end, quantum mechanical (QM) methods will be employed. The PhD student will first) assess the
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, deformation mechanisms and mechanical performance, ultimately enabling more efficient design and optimization of advanced structural materials. [1] https://www.pepr-diadem.fr/projet/ammetis-2/ [2] https
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mechanisms. The objective of this PhD project is to develop AI-based surrogate models for microstructure-aware macroscopic mechanical behavior by leveraging the large datasets generated within the AMMETIS