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The successful candidate will be responsible for: 1. Develop the numerical and analytical tools required to design these tunable random architectures and predict the mechanical behavior
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, · quantifying uncertainty in causal links, · integrating the resulting models into neural networks (or other machine learning models) to detect and predict anomalies or anticipate failures. The research
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properties and electrical characterization will be carried out. The results will be compared with ab initio calculations and will provide input for physical models based on real devices to predict key metrics
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