Robust low-dimensional representations for noisy real-world data
This project develops noise-resilient and generalisable AI models by combining low-rank adaptation and manifold learning to jointly model data, parameters, and uncertainty, enabling robust, efficient training on minimally curated real-world datasets with applications in healthcare, telecoms, and autonomy.
Start date
1 October 2026Duration
4 yearsApplication deadline
Funding source
EPSRC IDLA, NPLFunding information
- UKRI standard stipend: £25,805 for academic year 2026/27
- UK-level fees covered
- Generous research training support grant.
About
The project is in close collaboration with the National Physical Laboratory and benefits from the scientific environment and resources provided by the Centre for Vision, Speech and Signal Processing CVSSP and the Institute for People-Centred AI at the University of Surrey.
Eligibility criteria
- You will need to meet the minimum entry requirements for our PhD programme.
- A First Class undergraduate degree or MSc with Distinction (or equivalent overseas qualification) in mathematics, computer science, physics or engineering.
- Excellent mathematical, analytic, and programming skills
- Previous experience in AI
- Previous experience in tomographic imaging would be advantageous
- Open to candidates who pay UK/home rate fees. See UKCISA for further information.
How to apply
Applications should be submitted via the Vision, Speech and Signal Processing PhD programme page. In place of a research proposal, you should upload a document stating the title of the project that you wish to apply for and the name of the relevant supervisor.
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