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Field
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the development of a Virtual Training Environment (VTE) for disaster response simulation, integration of Building Information Modelling (BIM) with Structural Health Monitoring (SHM) using smart sensor networks, and
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Collaborative Doctoral Project (PhD Position) - AI-guided design of scaffold-free DNA nanostructures
DNA thermodynamic database, coarse-grained simulations of DNA motifs, and existing experimental data to establish an AI model that is able to guide the construction of desired secondary structures
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state-of-the-art high heat flux testing, simulating the extreme environments of fusion reactors. Harness advanced computational tools to model complex particle-material interactions and predict material
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the resilience of offshore marine infrastructures exposed to harsh and extreme environmental conditions. Through this PhD scholarship, you will contribute to the development of a physics-informed and data-driven
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on damage modelling. Calculation of linear and nonlinear response of offshore structures exposed to various loading scenarios including operational and extreme environmental conditions Development of accurate
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link structure-property relationships from DFT, MD, phase-field, TEM/SEM, and other multimodal datasets from simulation and experiment Develop benchmarking protocols and toolkits to evaluate AI models
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response simulation, integration of Building Information Modelling (BIM) with Structural Health Monitoring (SHM) using smart sensor networks, and resilience-informed design platforms. Furthermore, REUNATECH
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Environment (VTE) for disaster response simulation, integration of Building Information Modelling (BIM) with Structural Health Monitoring (SHM) using smart sensor networks, and resilience-informed design
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computing to develop a continuous and local alternative to existing gradient-based learning rules, bridging theories of predictive coding with event-based control/ Simulate models of the learning algorithm
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Inria, the French national research institute for the digital sciences | Saint Martin, Midi Pyrenees | France | about 5 hours ago
that drivers satisfy the defined safety properties. Expected outcomes include a better understanding of the conditions under which drivers can be memory-safe, formal models or specifications of key driver–kernel