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University of Southampton

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PhD in AI-Enhanced X-ray CT for Defect Detection in Advanced Manufacturing University of Southampton in United Kingdom

Degree Level

PhD

Field of study

Computer Science

Funding

Full funding available

Deadline

Aug 31, 2026

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Country

United Kingdom

University

University of Southampton

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Keywords

Computer Science
Biomedical Engineering
Mechanical Engineering
Materials Science
Artificial Intelligence
Manufacturing Engineering
Computer Vision
Fault Detection
X-ray Imaging
Machine learning

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About this position

PhD opportunity at the University of Southampton in the Faculty of Engineering and Physical Sciences on AI-Enhanced X-ray CT for Defect Detection in Advanced Manufacturing.

This project sits at the intersection of computer vision, machine learning, X-ray computed tomography (X-ray CT), manufacturing engineering, and mechanical engineering. The research aims to build advanced 3D AI methods for automated defect detection, classification, and quantification in X-ray CT datasets of advanced manufactured components, including metal additive manufacturing parts. The goal is a robust inspection pipeline that improves measurement consistency, reduces human error, and supports next-generation quality assurance in high-value manufacturing.

The project is supervised by Dr Joseph Lifton at the University of Southampton. The post is advertised as a competition funded PhD project for students worldwide. Funding options mentioned include Horizon Europe fee waivers, University Presidential Bursaries, and competition-based studentships that may cover UK-level tuition fees and a living stipend for top-ranked applicants.

Eligibility highlights include a UK 2:1 honours degree or international equivalent, with strong programming skills in Python or MATLAB. Helpful background includes machine learning, image processing, computer vision, CAD, manufacturing processes, or engineering metrology. English language qualification is required if applicable.

Applications are made through the University of Southampton portal. The instructions say to choose Research, 2026/27, Faculty of Engineering and Physical Sciences, select full-time or part-time, search for PhD Engineering & the Environment (7175), and add the supervisor name in section 2. The page notes that funding is awarded on a rolling basis, so early application is encouraged.

For questions, the page lists feps-pgr-apply@soton.ac.uk for general enquiries and J.J.Lifton@soton.ac.uk for an initial conversation with the project leader.

Funding details

Full funding including tuition fees and living expenses is available for this position. The scholarship covers all educational costs and provides a monthly stipend.

How to apply

Please submit your application including a cover letter, CV, academic transcripts, and contact information for two references. Applications should be sent via the online portal before the deadline.

More information can be found here

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