Summary
This PhD scholarship provides an opportunity to develop AI-driven ultrasonic methods for materials evaluation, focusing on fast AI surrogate models and inverse models for material properties extraction. Candidates will engage in simulation, experimental work, and machine learning within a vibrant research center.
Designation
Postgraduate Research PhD Project: AI-Driven Ultrasound for Materials Evaluation (2026)
| Category | Details |
|---|---|
| Research Area | AI and Ultrasonic Methods for Materials Evaluation |
| Location | University of Sussex |
| Eligibility/Qualification | – Applicants with a 2:1 or equivalent degree in Physics, Engineering, Applied Mathematics, Materials Science, or Computer Science. – Desirable but not essential experience includes ultrasound physics, numerical simulation, Python programming, and ML frameworks. |
| Job Description | The PhD project will involve: – Building and validating models for ultrasonic measurements. – Working in experimental and simulation settings to generate training datasets and benchmarking machine learning architectures. – Target application areas include metals, layered structures, and additively manufactured components. |
| How to Apply | – Apply online for the PhD in Informatics starting in September 2026. – Include a research proposal, CV, degree certificates and transcripts, and two references. – State explicitly that you are applying for the AI-driven ultrasound for materials evaluation studentship under Dr. Ming Huang’s supervision. |
| Last Date for Application | 08 June 2026, 23:45 (GMT) |
Contact Information
For practical questions regarding the application, contact: FoSEM-PGR@sussex.ac.uk
For academic inquiries, reach out at: ming.huang@sussex.ac.uk
