Job offer

• Perform numerical modelling of the three NDE techniques to evaluate the influence of relevant material property gradients on each NDE observable generating a sizable synthetic training datasets;
• Design and carry out laboratory experiments to produce representative experimental training data;
• Develop physics-informed machine learning algorithms, trained on both numerical simulations and experimental measurements (using a transfer learning approach), to recover quantitative material property gradients [2],[3],[4];
• Demonstrate the utility of the algorithms in a field-scale experiment on a metric-scale concrete wall, using the multi-physics NDE probe integrated onto drone platforms.

Master Degree or equivalent, Master Degree or equivalent

Research Field Mathematics » Applied mathematics

Education Level Master Degree or equivalent

Specific Requirements

• Wave propagation physics (acoustic, seismic, ultrasonic, electromagnetic) and/or diffusive phenomena (e.g., electrical resistivity).
• Strong programming skills either Python, MATLAB, julia or other scientific computing environments.
• Experience with numerical modelling techniques, such as finite difference, finite element, or spectral element methods.
• Interest in inverse problem formulation and solving and/or artificial intelligence techniques in the context of physical modelling.
• Proficiency in signal and data processing, including time- and frequency-domain analysis.
• Familiarity with instrumentation for non-destructive testing and/or sensing technologies.

Languages ENGLISH

As a full-time Doctoral Candidate connected to the European RADIANCE project, you will have the opportunity to:

• Participate in experiments with drones carrying an innovative multi-physic probe
• Access to a set of existing homemade experimental NDE equipments and numerical tools to validate your developments
• Work alongside leading colleagues in the field of NDT and Machine Learning (including in collaboration with Prof. Parisa Shokouhi, Penn State, USA).
• Properly communicate and disseminate your research results
• Publish your results in high profile open access journals and conferences

Selection process