GRADnet

Industrial collaborative PhD projects

PhD Scholarships – Radiation Detection Doctoral Network

Industrial collaborative PhD projects

The Radiation Detection Doctoral Network is a new collaborative doctoral training programme that provides industrially-relevant PhD research projects. The network is hosted by the Universities of Surrey, Sussex and Royal Holloway, in collaboration with our industrial partners National Physical Laboratory, Kromek, Hilger Crystals, Ultra Energy and Rapiscan Systems.

Project 1: Statistical Techniques and Machine Learning for Radiation Detection (Royal Holloway University of London, in collaboration with NPL and Ultra-Electronics)

The project will focus on applying techniques developed in particle physics to real-world monitoring applications such as continuous air monitors using in the nuclear industry. This project will develop a deliverable product for isotope recognition, using advanced statistical techniques and machine learning and considering in-situ calibration of networked sensors.

Project 2: Investigation of the stability of Silicon Photomultiplier based gamma and neutron detectors (University of Surrey, with NPL and Kromek )

This project will study the stability and performance of silicon photomultipliers (SiPMs) and their application to a new generation of handheld detector systems. The effect of external conditions on SiPM performance will be investigated (eg. temperature, humidity) and applications in homeland security and environmental monitoring will be developed.

Project 3: Next generation scintillator-based detector arrays for fast CT systems (University of Sussex, Rapiscan Systems and Hilger Crystals)

This project will identify next generation scintillator-based detector arrays for fast CT imaging systems, investigating scintillator performance and manufacturing processes and developing systematic testing protocols. The study will include detailed computer (GEANT4) simulations of optical transport and radiation deposition processes in scintillator materials.