Deep-Learning for Scatter Tomography

X-ray Scatter Tomography (ST) is emerging as a powerful imaging technique with implications for biomedical, security or material characterisation applications.   It is based on detecting scattered (rather than transmitted) radiation, which enables retrieving characteristics of the sample otherwise not possible. 

This project aims to further develop ST by applying deep learning to address challenges such as image reconstruction with noisy and incomplete data, and to derive, implement, and validate new AI-based image reconstruction algorithms 

The project 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 and from collaboration with the  Foreign, Commonwealth and Development Office (FCDO) and the National Physical Laboratory (NPL). The researchers can also spend time on site at NPL and  be part of the wider  collaborative network between NPL,  University of Surrey, and the University of Strathclyde. A generous stipend is offered in addition to funding for tuition fees and research training. 

We are looking for applicants with a degree in Computer Science, Mathematics, Physics, or Electrical Engineering.  Prior experience in tomographic imaging  would be advantageous but is not required.  The scholarship is primarily open to UK nationals, but EU, Commonwealth  or USA nationals that qualify to pay UK-level (home) tuition fees may also be considered. 

You will need to meet the minimum entry requirements for Vision, Speech and signal processing PhD programme.

Applicants should have:

• 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 tomographic imaging would be advantageous. 

Open to UK nationals and those who pay UK/home rate fees. See UKCISA for further information.