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that enables cohesive operation of the design and production system. This position is part of the EIC Pathfinder Project AM2PM: “Additive to Predictive Manufacturing for Multistorey Construction using Learning
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collaborate closely with a postdoctoral researcher responsible for in-situ fatigue testing under corrosive environments, and will participate in the 4D (x,y,z,time) analysis of the AM microstructure and crack
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, evaluating, and fine-tuning machine learning models (e.g. deep neural networks) to segment underwater scenes and classify anomalies. The work will explore the use of virtual environments and synthetic datasets
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