SHORT DESCRIPTION

PhD candidate or Post-doctoral research associate - Artificial Intelligence applied to enhancement of X-ray Computed Tomography


OTHER DETAILS

Ref. num. 2024-FS-R1-135

PhD candidate or Post-doctoral research associate - Artificial Intelligence applied to enhancement of X-ray Computed Tomography


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.


Description

The candidate will participate in a public funded research project (METALIA – “Enabling technologies for the implementation of Artificial Intelligence in the value chain of the Additive Manufacturing of new metal alloys”) aiming at developing materials for various applications (space, biomedical, aeronautic, etc.) by additive manufacturing (AM). This PhD/Post-doc focuses on enhancing the capabilities of XCT (X-ray Computed Tomography) technique by applying artificial intelligence to the reconstruction of the volumes, noise reduction and defect segmentation, classification and analysis.

XCT is one of the most powerful techniques for defect assessments of additive manufacturing materials as it comprises a high resolution for the typical defect types in AM, a large volume of inspection which allows detecting thousands of defects at once, provides three-dimensional information of the inspected material and it is non-destructive. Despite the advantages, XCT is a relatively slow, and therefore costly, technique due to the large number of projections (radiographs from different angle positions) required to provide a high-quality volume reconstruction. Additionally, when measuring materials with high X-ray absorption such as metals, noise and artifacts are generated in the images. Common data limitations during XCT experiments include: i) acquiring only a limited number of projections; ii) noise in the projection images; and iii) acquiring projections for a limited angular range. Thus, the main activity of the candidate within the project will correspond to data analysis, and the development and implementation of AI-based tools to enhance and accelerate XCT pre- and post-processing. Solutions will be implemented in both, laboratory and synchrotron XCT data.

The candidate is expected to have a solid background in programming, artificial intelligence and data processing.


Requirements

For PhD candidates, the position is most appropriate for recent master's graduates (or soon to graduate) in fields related to machine learning, computer science, material science or related disciplines with excellent academic credentials pursuing a PhD in application of artificial intelligence for image processing.

Post-doctoral candidates with experience in AI applied to material science and/or XCT are also welcome to apply.

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.

Knowledge of machine learning, data analysis, image and signal treatment.

Full proficiency in English, oral and written, is mandatory.

3.5 years contract with 1 year evaluation period.

Interested candidates should submit their Curriculum Vitae, a brief cover letter addressing their motivation, as well as academic credentials.


Conditions

- Full-time contract including social security coverage.

- The post will remain active and open until filled.

- Expected start date: as soon as viable candidate is found.


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.