Computer Science, Aerospace Engineering: Fully Funded PhD Studentship in AI Models for Efficient Non-destructive Testing (RS939)

Funding provider: EPSRC and TWI 

Funding duration: 4 years

Subject areas: Computer Science, Aerospace Engineering, Civil Engineering, Physics

Project start date:  1 July 2026 ** (Please see the note below regarding potential later start dates.)

Supervisors: 

• Professor Chenfeng Li (First Supervisor) 
• Professor Richard Johnston (Second Supervisor)

Aligned programme of study: PhD in Computer Science

Mode of study: Full-time

Project description: 

Are you passionate about artificial intelligence, data analytics, and cutting-edge engineering applications? Join our interdisciplinary research team and contribute to the future of Non-Destructive Testing (NDT) – a crucial technique used in industries to assess materials, components, and structures without causing damage.

This PhD project focuses on advancing Ultrasound Testing and X-ray Computed Tomography (CT) – two key NDT techniques used to inspect metallic and composite materials. These methods generate large 3D datasets that can be difficult for human experts to analyse manually, increasing the risk of missed defects.

Using the power of Artificial Intelligence (AI), this research aims to:

✅ Automate defect detection in complex 3D structural data

✅ Enhance diagnostic accuracy and processing speed

✅ Provide human experts with a reliable second opinion

This project integrates image processing, data analytics, machine learning, and computational modelling, with applications in aerospace, mechanical, civil, and materials engineering.

 We welcome applicants with a background in:

🔹 Computer Science

🔹 Aerospace Engineering

🔹 Civil Engineering

🔹 Physics

 If you have a keen interest in AI, data science, or computational modelling and want to collaborate with industry experts, this opportunity is for you!

 Why Join Us?

✔ Work with a leading research team and industry specialists

✔ Gain interdisciplinary training in AI, modelling, and data analytics

✔ Contribute to real-world engineering applications

✔ Be part of the dynamic research community at the Zienkiewicz Institute for Modelling, Data and AI

Note for international and European applicants: details of how your qualification compares to the published academic entry requirements can be found on our Country Specific Entry Requirements page.

PhD: Applicants for PhD must hold an undergraduate degree at 2.1 level in Computer Science, Mathematics or a closely related discipline, or an appropriate master’s degree with a minimum overall grade at ‘Merit’ (or Non-UK equivalent as defined by Swansea University).

English Language
IELTS 6.5 Overall (with no individual component below 6.0) or Swansea University recognised equivalent. Full details of our English Language policy, including certificate time validity, can be found here.

This scholarship covers the full cost of tuition fees and an annual stipend at UKRI rate (currently £21,805 for 2026/27) and an annual top of  £1200. 

Additional research expenses of up to £1,000 per year will also be available. 

To apply, please complete the entire application form 

In order to be considered for this scholarship award the following steps are also required. 

1. In section ‘Programme Related Information’ please input the relevant RS Code for the scholarship award i.e. RS939
2. In section ‘Research’ you will see ‘Proposed project title/studentship title’* (Mandatory) 
   • In ‘Proposed project title/studentship title’ please input both:  
     
     • the RS Code, RS939 and  
     • the scholarship title.   
   • Please leave Proposed Supervisor field blank 
   • Please leave Research Project (if applicable) blank 
   • In ‘Do you have a proposal to upload?*’(Mandatory) Please select Yes 
   • Then upload copy of advert (you can save the advert by clicking print, and then print to pdf) 
3. In section ‘Funding information’ please choose the option ‘Scholarship Funding’ only. Please ensure no other options are selected.  

*It is the responsibility of the applicant to list the above information accurately when applying, please note that applications received without the above information listed will not be considered for the scholarship award. 

If you’ve previously applied for this programme, the system will display an “Application Submitted” warning and block a new submission. In this case:

1. Apply for the same course with the next available start date (e.g., select January if October is unavailable).
2. Email pgrscholarships@swansea.ac.uk with your student number and the relevant scholarship RS code, requesting the start date be amended to match the advert.
3. Admissions staff will then update your application accordingly.

One application is required per individual Swansea University led research scholarship award; applications cannot be considered listing multiple Swansea University led research scholarship awards. 

NOTE:  Applicants for PhD/EngD/ProfD/EdD - to support our commitment to providing an environment free of discrimination and celebrating diversity at Swansea University you are required to complete an Equality, Diversity and Inclusion (EDI) Monitoring Form in addition to your programme application form.    

Please note that completion of the EDI Monitoring Form is mandatory; your application may not progress if this information is not submitted. 

As part of your online application, you MUST upload the following documents (please do not send these via email): 

• CV 

• Degree certificates and transcripts (if you are currently studying for a degree, screenshots of your grades to date are sufficient) 

• A cover letter including a ‘Supplementary Personal Statement’ to explain why the position particularly matches your skills and experience and how you choose to develop the project. 

• One reference (academic or previous employer) on headed paper or using the Swansea University reference form. Please note that we are not able to accept references received citing private email accounts, e.g. Hotmail. Referees should cite their employment email address for verification of reference. 

• Evidence of meeting English Language requirement (if applicable). 

• Copy of  UK resident visa (if applicable) 

• Confirmation of  EDI form submission 

Informal enquiries are welcome; please contact Prof. Chenfeng Li c.f.li@swansea.ac.uk 

*External Partner Application Data Sharing – Please note that as part of the scholarship application selection process, application data sharing may occur with external partners outside of the University, when joint/co- funding of a scholarship project is applicable. 

** In exceptional circumstances, and subject to the discretion of the University and/or the relevant funding body, a deferral of offer may be granted to the next available enrolment period. Such deferral will typically not exceed a duration of three calendar months from the originally stipulated commencement date. Please note that only one deferral may be considered, and any such deferral is not guaranteed.