pFIDAMC seeks a Doctoral Candidate to develop machine learning tools for automated identification, classification, and quantification of defects in composite materials, using high- and low-resolution inspection data. You will train models with XRM and ultrasonic imaging data, and contribute to scholarly publications and international conferences. /ppThe role requires a Master’s degree, English proficiency, and admission to a European doctoral program; collaboration within the LEGEND network is /p #J-18808-Ljbffr
📌 PhD Candidate: AI for Automated Defect ID in Composites (Getafe)
🏢 FIDAMC
📍 Getafe
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