PhD Candidate: AI for Automated Defect ID in Composites

FIDAMC 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.
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You will train models with XRM and ultrasonic imaging data, and contribute to scholarly publications and international conferences.

The role requires a Master’s degree, xqbhyrx English proficiency, and admission to a European doctoral program; collaboration within the LEGEND network is