SHORT DESCRIPTION
The presence of defects in carbon fibre reinforced composite materials is a common manufacturing defect that could endanger the in-service performance of components. Composite materials are usually inspected by ultrasonic testing. The use of machine learning models could discover the hidden patterns of the interaction between the defects and the ultrasound wave. On the other hand, X-ray tomography (XCT) is by far the best technique for non-destructive damage assessment in composite materials, being able to identify in 3D manufacturing defects.The use of machine learning models could discover the hidden patterns of the interaction between the defects and the ultrasound wave. XCT will be used as ground through and to benchmark the results from machine learning models.
OTHER DETAILS
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IMDEA Materials Institute is a public research organization founded in 2007 by Madrid’s regional government to carry out research of excellence in Material Science and Engineering by attracting talent from all over the world to work in an international and multidisciplinary environment. IMDEA Materials has grown rapidly since its foundation and currently includes more than 120 researchers from 22 nationalities and has become one of the leading research centers in materials in Europe which has received the María de Maeztu seal of excellence from the Spanish government. The research activities have been focused on the areas of materials for transport, energy, and health care and the Institute has state-of-the-art facilities for processing, characterization and simulation of advanced materials.
More information can be found at our webpage.
The work involves material testing, ultrasonic inspection, X-ray characterization, data analysis and programming. Therefore, a high interest in programming is mandatory. Some programming knowledge (preferable in python) is desirable, as well as in artificial intelligence techniques, data visualization, image analysis.
In this study, the candidate main task is to develop AI-based model for defect identification in composite materials, from ultrasonic and XCT inspection data. In detail, the main research tasks include:
The position is most appropriate for recent master's graduates (or soon to graduate) in fields related to informatics, masters in AI, material science and engineering, or related disciplines with excellent academic credentials pursuing a PhD in computer science and AI.
Experience or knowledge in AI applied to XCT images or any other image is highly valuable. Close interactions with industrial stakeholders are expected; therefore, the ability to work as part of a team is essential.
Programming knowledge in any language, preferably Python for compatibility with already developed work will be valued.
Full proficiency in English, oral and written, is mandatory.
Interested candidates should submit their Curriculum Vitae, a brief cover letter addressing their motivation, as well as academic credentials.
ADDITIONAL INFORMATION
Contract financed by the Young Researchers Programme of the Community of Madrid / Contrato financiado por el Programa de Jóvenes Investigadores, de la Comunidad de Madrid.
Candidates must meet the following criteria:
- 1 years contract. Extension possible.
- Full-time contract including social security coverage.
- The post will remain active and open until filled.
Applications are processed upon reception. The position might be closed once ten working days have passed since publication, so we encourage early application.
The working language of the Institute is English. Full command of the English language is required in all positions.
WHAT YOU WILL FIND AT IMDEA:
Stimulating environment where you can grow professionally.
IMDEA Materials Institute is committed to equal opportunities, diversity and the promotion of a healthy work environment and work-life balance. Female applicants are encouraged to apply to our research and technical positions. See our Gender Equality Plan here and our Code of Ethics here.
Besides on-the-job technical training, IMDEA Materials Institute is committed to training the Institute’s scientists and staff in “soft” or transversal skills. See the available training here.
Meet some of our alumni to see what it is like to work with us.