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detection and automation. The UMLFF project aims to develop next-generation MLFFs with built-in uncertainty predictions to enable safe, automated active learning and create broad, reliable MLFFs. You will
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AI4TECS aims to develop the first AI‑powerAd system that integrates real‑time EC identification using non-target high resolution mass spectrometry data, toxicity prediction, and transformation modelling
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currently lack reliable uncertainty estimates, limiting error detection and automation. The UMLFF project aims to develop next-generation MLFFs with built-in uncertainty predictions to enable safe, automated
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for anisotropic laminae and laminates (e.g., layer-wise / higher-order plate models) to accurately predict stress fields and assess cloaking performance. Build a staggered multi-scale simulation workflow (from