FTE: 1 (35 hours/week)
Term: Fixed (12 months)
Closing Date: 22 November 2020
The Centre for Ultrasonic Engineering (CUE), based in the Department of Electronic & Electrical Engineering (EEE) at the University of Strathclyde is seeking to recruit a Research Associate to work in conjunction with the Department of Mathematics and Statistics and participate in a multi-partner collaborative research project focused on tackling the inverse problems associated with in-process ultrasonic Non-Destructive Testing (NDT) of fusion welding and Wire + Arc Additive Manufacturing (WAAM) components.
Traditionally in fusion welding or WAAM metal 3D printing, inspection of the structure is a distinctly separate manufacturing process that occurs when the build of a component is complete. This ultimately limits productivity and throughput along with increased re-work if defects are detected post-build especially in multi-layer builds. The ultimate aim of this research is to investigate the potential of embedding ultrasonic inspection techniques directly at the point of deposition to deliver high-quality components right, first time. To maximise the reliability of these inspections, it is vital that wave propagation within these complex samples is well understood so that the collected ultrasonic inspection data can be analysed and inverted to produce characterisations of the spatially varying material properties within the sample, subsequently enhancing defect detection and characterisation capabilities.
Daily activities within the role will include running simulations of ultrasonic wave propagation within weld materials, developing efficient models of wave propagation in complex media, researching and implementing appropriate inversion and optimisation strategies and testing these on both simulated and experimentally collected data. Scientific publication and dissemination of results will be required, through both academic journals and conferences.
To be considered for the role, you will be educated to a minimum of Masters (preferably PhD) level in a relevant subject (e.g. physics, mathematics, engineering); or have equivalent relevant experience in addition to a relevant Degree. You will have demonstrable capability in mathematical modelling and computer programming and the ability to conduct individual research work and disseminate results. You will have excellent written and verbal communication skills, with an ability to listen, engage and persuade and to present complex information in an accessible way to a range of audiences, and you will have the ability to work as part of a team, integrating with existing research team members and collaborating effectively with both academic and industrial partners.
For informal enquiries, please contact Dr Charles MacLeod, Senior Lecturer, [email protected]