University of Southampton
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PhD in Deep Equilibrium Machine Learning for X-ray Tomographic Image Reconstruction University of Southampton in United Kingdom
Degree Level
PhD
Field of study
Computer Science
Funding
Potential funding is available for the strongest candidates through the Faculty of Engineering and Physical Sciences graduate school studentship programme. Funding is competitive. The page also mentions funding opportunities for UK and international students, Horizon Europe fee waivers covering the difference between overseas and UK fees for qualifying students, Presidential Bursaries covering the difference between overseas and UK fees for top-ranked applicants, and competition-based studentshi
Deadline
Jan 29, 2027
Country
United Kingdom
University
University of Southampton
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About this position
PhD opportunity at the University of Southampton in deep equilibrium machine learning models for the efficient reconstruction of X-ray tomographic images.
This project sits at the intersection of machine learning, computer vision, inverse problems, optimization, applied mathematics, and X-ray physics. The goal is to develop advanced AI tools that convert real X-ray measurement data into artefact-free 3D images, with a focus on realistic X-ray tomography (XCT) settings and large datasets.
You will explore recently introduced deep equilibrium models for image reconstruction, addressing challenges such as limited measurements, image noise, artefacts, computational efficiency, and the lack of training data in many practical settings. The work is primarily computational, but there is also the opportunity to engage with the University of Southampton’s dedicated X-ray Computed Tomography centre, µ-VIS, part of the UK’s National facility for XCT.
The project is supervised by Professor Thomas Blumensath and Dr Richard Boardman at the University of Southampton in the United Kingdom.
Funding: Potential funding may be available for the strongest candidates through the Faculty of Engineering and Physical Sciences graduate school studentship programme. The page also mentions fee-waiver and studentship opportunities for UK and international applicants, including Horizon Europe fee waivers and competition-based bursaries/studentships.
Eligibility: Applicants should hold at least a UK 2:1 honours degree or international equivalent; a first-class honours degree or equivalent is preferred. English language qualification is required if applicable.
How to apply: Submit an online application for the Research programme (2027/28), choose full-time or part-time, search for PhD Engineering & the Environment (7175), and add the supervisor name in section 2. Include a CV, two academic references, transcripts/certificates, and English language evidence if needed.
Deadline: 2027-01-29.
Funding details
Potential funding is available for the strongest candidates through the Faculty of Engineering and Physical Sciences graduate school studentship programme. Funding is competitive. The page also mentions funding opportunities for UK and international students, Horizon Europe fee waivers covering the difference between overseas and UK fees for qualifying students, Presidential Bursaries covering the difference between overseas and UK fees for top-ranked applicants, and competition-based studentshi
What's required
Applicants should have a UK 2:1 honours degree or international equivalent, and preferably a very good undergraduate degree with at least a 1st class honours degree or international equivalent. English language qualification is required if applicable. The project is aimed at strong candidates with computational and quantitative preparation.
How to apply
Apply online by selecting Research programme type for 2027/28, choosing full time or part time, searching for PhD Engineering & the Environment (7175), and adding the supervisor name in section 2. Prepare a CV, two academic references, degree transcripts/certificates, and an English language qualification if applicable. For questions, contact [email protected] or [email protected].
More information can be found here
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