Data-driven polarimetric shape sensing of composite laminates

This PhD studentship, supported by the Net²Zero Centre for Doctoral Training, is based at the Aston Institute of Photonic Technologies, Aston University, Birmingham, UK. The successful candidate will join a dynamic experimental group focused on advancing fibre optic sensing technologies for structural health monitoring (SHM) and shape sensing. SHM is crucial for the safety and reliability of engineering structures such as bridges, wind turbines, aircraft, and civil infrastructure, while shape sensing is increasingly important in robotics, human motion analysis, and surgical instrumentation. The project addresses limitations in current Fibre Bragg Grating (FBG) sensor systems, which, despite their high resolution and robustness, struggle with cost-effective, high-resolution localisation, defect identification, and predictive modelling. In collaboration with industry partners Airbus, Insensys, and Target3D, the research aims to develop and validate an AI-driven polarimetric dual optical frequency comb (DOFC) technique for monitoring structural defects in composite laminates used in aerospace and renewable energy sectors. By integrating advanced photonic sensing with machine learning, the project will deliver enhanced localisation and classification of defects, predictive modelling of defect evolution under operational conditions, and cost-effective sensing solutions adaptable to industrial environments. The outcomes are expected to significantly advance shape sensing technologies and optical frequency comb applications, with strong potential for industrial adoption and societal benefit in sustainable energy and aerospace safety. Applicants should hold, or expect to achieve, a First Class or 2.1 Bachelor’s degree in a relevant subject, or a Bachelor’s degree (First Class or 2.1) plus a Master’s degree (Merit or higher). Equivalent international qualifications are accepted. Essential qualifications include a strong foundation in physical optics and photonics, and the ability to work independently and collaboratively. Desirable skills include scientific programming, computational methods, mathematical modelling, numerical analysis, simulation of physical systems, background in differential equations, mathematical physics, advanced data analysis, and prior exposure to experimental optics or fibre sensing technologies. English language proficiency is required; evidence can be submitted later if not currently available. The studentship covers tuition fees and provides an annual maintenance allowance. The position is based on the Aston Campus, and regular in-person attendance is expected. Interviews will be conducted online via Microsoft Teams. For formal enquiries, contact Assoc. Prof. Sergey Sergeyev at [email protected]. For application process queries, contact [email protected]. To apply, submit a complete application including transcripts, certificates, research statement, personal statement, CV, two academic references, evidence of English language proficiency, and a copy of your passport. Applications missing documents will be automatically rejected. Apply via the provided online links.