Phd Candidate: Ai For Automated Defect Id In Composites
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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.
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, English proficiency, and admission to a European doctoral program; collaboration within the LEGEND network is
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PhD Candidate: AI for Automated Defect ID in Composites
Hace 15 horas
getafe, comunidad de madrid, España FIDAMC Jornada completaFIDAMC 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. The role...
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Getafe, Comunidad de Madrid, Area Metropolitana (comarca); Comunidad de Madrid, España Fidamc Jornada completaFIDAMC 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.The role...
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Getafe, Madrid, España FIDAMC Jornada completaFIDAMC 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.The role...
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Getafe, Madrid, España FIDAMC Jornada completaFIDAMC 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.The role...
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getafe, comunidad de madrid, España Fidamc Jornada completaThe Doctoral Candidate will be expected to develop Machine Learning tools that enable automated, objective and efficient identification, classification and quantification (ICQ) and spatial mapping of meso- and macro-scale defects in composite materials, through training on coupled high-resolution and low-resolution non-destructive inspection data (XRM and...
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getafe, comunidad de madrid, España FIDAMC Jornada completaThe Doctoral Candidate will be expected to develop Machine Learning tools that enable automated, objective and efficient identification, classification and quantification (ICQ) and spatial mapping of meso- and macro-scale defects in composite materials, through training on coupled high-resolution and low-resolution non‑destructive inspection data (XRM and...
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Getafe, Madrid, España FIDAMC Jornada completaThe Doctoral Candidate will be expected to develop Machine Learning tools that enable automated, objective and efficient identification, classification and quantification (ICQ) and spatial mapping of meso- and macro-scale defects in composite materials, through training on coupled high-resolution and low-resolution non‑destructive inspection data (XRM and...
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Getafe, Comunidad de Madrid, España Fidamc Jornada completaFIDAMC 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.Si desea conocer los requisitos para este puesto, siga leyendo para obtener toda la información relevante.You will train models with XRM and...
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getafe, madrid, España FIDAMC Jornada completaThe Doctoral Candidate will be expected to develop Machine Learning tools that enable automated, objective and efficient identification, classification and quantification (ICQ) and spatial mapping of meso- and macro-scale defects in composite materials, through training on coupled high-resolution and low-resolution non‑destructive inspection data (XRM and...