PhD in Machine Learning for NDE Inspection

University of Strathclyde

Department of Electronic and Electrical Engineering

Project Description

Fully Funded – Enhanced Stipend – Industry Sponsored

EPSRC CDT in Future Innovation in Non-Destructive Evaluation

The University of Strathclyde is offering a fully funded (with enhanced stipend) PhD studentship in the area of Machine Learning, to a suitably qualified student with a background in engineering/ physics/ computer science and programming. You will have access to state-of-the art deep learning hardware and high speed ultrasonic testing equipment, to interpret ultrasonic non-destructive evaluation (NDE) measurements for industrial applications in aerospace.

You will have an interest in machine learning/ statistical pattern recognition/ image processing and ideally ultrasonic measurement systems. The studentship is incorporated in the FIND CDT, https://www.find-cdt.ac.uk/ giving you access to a wide range of training and networking opportunities. The training covers both technical and transferable skills. The networking includes an annual student conference as well as technology transfer workshops with industry.

Working with our global aerospace partner (Spirit AeroSystems) – you will have opportunity to integrate and network globally to conduct high quality novel research linked closely to industry applications and impact. Typical applications areas are in ultrasonic non-destructive evaluation (NDE) of composite materials used in wing and fuselage fabrication.

You will work with an established and dynamic team of researchers in the new robotics hub established at Strathclyde University dedicated to in-process automated sensing and linked to a new Research Chair sponsored by the Royal Academy of Engineering and Spirit AeroSystems Ltd.

This new facility is a £2.6M state-of–the art robotics and sensing hub that supports non-destructive testing and measurement in the Centre for Ultrasonic Engineering (CUE). The lab is closely linked with the National Manufacturing Institute for Scotland (NMIS), https://www.nmis.scot/ and the new Aerospace Innovation Centre established by Spirit AeroSystems at their Prestwick manufacturing facility.

Funding Information

Fully Funded – Enhanced Stipend – Industry Sponsored

Excellent arrangements for travel / conference attendance.

The studentship is incorporated in the FIND CDT, https://www.find-cdt.ac.uk/ giving you access to a wide range of training and networking opportunities. The training covers both technical and transferable skills. The networking includes an annual student conference as well as technology transfer workshops with industry.

Eligibility Requirements

Applications are welcomed from a wide variety of disciplines and experience; you will have an engineering/ physics/ computer science and programming background; qualified to 1st class or 2(1) degree level.

Supplementary Information

Please contact Professor Gareth Pierce at Strathclyde for more details: [email protected]

To apply for this PhD, please email s.g.pierce@strath.ac.uk.

Before sending your email, please double check you have followed all guidelines in this listing and have included a reference number if asked to do so.

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