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University of Southampton

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PhD in Evaluating Defect Detectability for Iteratively Reconstructed Industrial X-ray Computed Tomography Data University of Southampton in United Kingdom

Degree Level

PhD

Field of study

Computer Science

Funding

Potential funding may be available through the Faculty of Engineering and Physical Sciences graduate school studentship programme on a highly competitive basis. Additional funding opportunities are mentioned for UK and international students, including Horizon Europe fee waivers covering the difference between overseas and UK fees for qualifying students, Presidential Bursaries covering the fee difference for top-ranked applicants, and competition-based studentships that typically cover UK-level

Deadline

Jan 29, 2027

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Country

United Kingdom

University

University of Southampton

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Keywords

Computer Science
Mechanical Engineering
Materials Science
Mathematics
Mathematical Modeling
Manufacturing Engineering
Computer Vision
Image Reconstruction
Optimization Algorithm
Physics
ML

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About this position

PhD opportunity at the University of Southampton in the Faculty of Engineering and Physical Sciences, working with the µ-VIS facility, a dedicated X-ray Computed Tomography (XCT) centre and part of the UK’s National Facility for lab-based XCT.

The project is titled Evaluating defect detectability for iteratively reconstructed industrial X-ray computed tomography data and focuses on industrial X-ray computed tomography, iterative reconstruction, machine learning, optimization algorithms, computer vision, mathematical modelling, and defect detectability in safety-critical manufactured components.

You will study how advanced reconstruction methods affect the quality of 3D images from XCT measurements, with the goal of improving visibility of internal defects that could compromise component safety. The work uses real and simulated tomography data and explores anisotropic resolution, noise, and parameter choices for iterative optimization and machine-learning-based reconstruction.

The supervisory team is Professor Thomas Blumensath, Dr Richard Boardman, and Dr Joseph Lifton. The project is linked to the University of Southampton’s µ-VIS facility, which has strong industrial connections and applications in aircraft crash investigations, Formula 1, space technology, and more.

This is a PhD opening and is advertised as a Competition Funded PhD Project (Students Worldwide). Funding is competitive and may be available through the Faculty of Engineering and Physical Sciences graduate school studentship programme. The post also mentions fee-waiver and bursary opportunities for eligible applicants.

Entry requirements: a UK 2:1 honours degree or international equivalent is required; a very good undergraduate degree, at least a UK 1st class honours degree or equivalent, is highlighted for strong candidates. English language qualification is needed if applicable.

Application window: the listing shows a date of Friday, January 29, 2027. Apply via the Southampton research application portal and include your CV, two academic references, transcripts/certificates, and English language evidence if needed.

Funding details

Potential funding may be available through the Faculty of Engineering and Physical Sciences graduate school studentship programme on a highly competitive basis. Additional funding opportunities are mentioned for UK and international students, including Horizon Europe fee waivers covering the difference between overseas and UK fees for qualifying students, Presidential Bursaries covering the fee difference for top-ranked applicants, and competition-based studentships that typically cover UK-level

What's required

A UK 2:1 honours degree or international equivalent is required, and a very good undergraduate degree with at least a UK 1st class honours degree or international equivalent is preferred/expected for strong consideration. Applicants should be suitable for research in computational mathematics, computer vision, machine learning, manufacturing engineering, mathematical modelling, medical physics, optical physics, or physics. English language qualification is required if applicable.

How to apply

Apply through the University of Southampton postgraduate research application portal. Choose programme type Research, academic year 2027/28, Faculty of Engineering and Physical Sciences, then select full time or part time and search for PhD Engineering & the Environment (7175). Add the supervisor name in section 2 and upload your CV, two academic references, transcripts/certificates, and English language qualification if applicable.

More information can be found here

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