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PhD Studentship: AI-Driven Ultrasound for Materials Evaluation (2026) University of Sussex in United Kingdom
Degree Level
PhD
Field of study
Computer Science
Funding
Full funding availableDeadline
Sep 11, 2026
Country
United Kingdom
University
University of Sussex

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About this position
This fully funded PhD studentship at the University of Sussex focuses on AI-driven ultrasound for materials evaluation, bringing together artificial intelligence, ultrasonic physics, simulation, and experimental validation. The project tackles a challenging inverse problem: using ultrasonic measurements to infer material properties or detect defects inside metals and layered structures. It is aimed at developing quantitative, transferable models that can learn from large-scale simulation data and then work on experimental measurements in the laboratory.
You will work on a research pipeline that spans simulation, model development, uncertainty quantification, and lab-based validation. The project includes running large ultrasound simulations to build training datasets, designing and benchmarking modern neural network architectures, and testing how well the models bridge the gap between simulation and real measurements. Access to advanced ultrasonic instrumentation, high-performance computing resources, and an active interdisciplinary research environment at Sussex will support the work.
The studentship is suitable for candidates with a strong background in physics, engineering, applied mathematics, materials science, computer science, or a related subject. Helpful experience includes ultrasound or wave physics, numerical simulation, Python, and machine learning frameworks, although these are not essential. The post is open to UK and international applicants.
Funding is for 3.5 years and includes a tax-free stipend of £21,805 per year, full tuition fee waiver at the UK or international rate, and a one-off Research and Training Support Grant of £2,000. The application deadline is 11 September 2026. This is a re-advertisement, so previous applicants do not need to apply again.
For informal enquiries, contact Dr Ming Huang or Dr Ivor Simpson. The project offers strong interdisciplinary training and the chance to publish, attend conferences, and collaborate with academic and industrial partners.
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.
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