Università degli studi di Perugia invites applications for a research position contributing to the SMS‐SAFEST project. You will develop advanced methodologies for structural health monitoring of smart masonry structures, focusing on static and seismic actions, and you will integrate data from smart bricks and mortars using machine learning for damage identification and classification.
The role also includes numerical modelling of full‐scale masonry structures and validation of SHM strategies, as
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📌 AI-Driven SHM for Smart Masonry Structures (Italia)
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📍 Italia
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