At a Glance
- Tasks: Develop AI-driven ultrasonic methods for evaluating materials and solving complex engineering problems.
- Company: Join a dynamic research centre at the University of Sussex, near Brighton.
- Benefits: Fully funded studentship with tuition coverage, stipend, and world-class supervision.
- Other info: Opportunities to publish, attend conferences, and collaborate with industry leaders.
- Why this job: Make a real impact using cutting-edge AI to solve important physics and engineering challenges.
- Qualifications: Strong degree in relevant fields; enthusiasm for interdisciplinary learning is key.
The predicted salary is between 19350 - 23650 £ per year.
Would you like to use cutting-edge artificial intelligence to solve real-world physics and engineering problems that matter? This fully funded PhD studentship offers an exceptional opportunity to do exactly that, working at the forefront of AI-driven ultrasonic evaluation of materials.
Ultrasound plays a critical role in keeping our world safe and reliable. From inspecting aircraft components and pipelines to monitoring batteries in electric vehicles, ultrasonic measurements let us “see” inside materials without damaging them. Yet interpreting the resulting signals is far from straightforward: waves in real materials behave in complex ways, and turning measurements back into quantitative information about a material’s internal state is a notoriously difficult inverse problem.
This is where AI can be a game changer. Deep learning models can learn the mapping between material states and ultrasonic responses from simulation data, delivering quantitative predictions once trained, and remarkably, can be transferred to work directly on experimental measurements.
In this PhD, you will develop AI-driven ultrasonic methods for quantitative materials evaluation, focusing on inverse models that extract material properties or defect information from measurements. You will work across the full research pipeline: running large-scale ultrasound simulations to generate rich training datasets, designing and benchmarking modern neural network architectures, quantifying the uncertainty of model predictions, and validating your models in our ultrasonic laboratory to bridge the simulation-to-experiment gap. Application areas include metals and layered structures.
You will join a dynamic and rapidly growing research centre at Sussex, with access to advanced ultrasonic instrumentation, high-performance computing resources, and a strong network of academic and industrial partners. Throughout your PhD, you will gain a highly valuable interdisciplinary skill set spanning ultrasonic physics, large-scale numerical simulation, experimental measurement, and state-of-the-art AI, opening up excellent career opportunities in academia, industry, and beyond.
What we are looking for:
We welcome applications from enthusiastic, curious, and self-motivated candidates with (or expecting) a strong undergraduate or Master's degree in physics, engineering, applied mathematics, materials science, computer science, or a related discipline. Prior experience in any of the following is a plus but not essential: ultrasound or wave physics, numerical simulation, Python programming, and machine learning frameworks. Most importantly, we are looking for someone who enjoys learning across disciplines, thinks creatively, and is keen to make real research impact.
What you will get:
- A fully funded studentship covering tuition fees and a stipend (open to UK and international applicants).
- World-class supervision and training in an interdisciplinary, research-active environment.
- Opportunities to publish in leading journals, attend international conferences, and collaborate with industry.
- A vibrant student community at the University of Sussex, located near the beautiful coastal city of Brighton.
PhD Studentship: AI-Driven Ultrasound for Materials Evaluation (2026) in Brighton employer: Technical University of Denmark
The University is an exceptional employer, offering a supportive and collaborative work environment that prioritises employee well-being and professional growth. With the flexibility of hybrid working and generous leave entitlements, including 36 days off, staff are encouraged to maintain a healthy work-life balance while contributing to the academic success of students in the Faculty of History.
Contact Details:
Technical University of Denmark Recruitment Team
