This project is fully funded by an industrial CASE award with the National Nuclear Laboratory (NNL) and is to develop hyperspectral imaging for a wide range of applications in the nuclear sector. One of these is to go on a robotic platform to survey sites for decommissioning and is part of the TORONE project (www.torone-project.com). You will develop data analytics routines involving artificial intelligence and machine learning to analyse the images. The studentship will be associated with the GREEN CDT (Growing skills for reliable economic energy from nuclear).
Rapid decision making during nuclear decommissioning and radioactive waste management, including deep geological disposal, is key to reducing risk and costs. This project aims to develop the capability to undertake speedy, remote, in-situ mapping of materials in extreme environments using hyperspectral imaging in 3D, through (i) integration with 3D digital data (e.g. from 3D laser scanning) and (ii) the use of photogrammetry-style techniques to create 3D hyperspectral material images without the need for 3D geometrical data collection. This will be undertaken within the framework of a GIS-style spatial database building management system (DBMS) to set the 3D context, and allow real-time decision making for safety cases.
The student will receive tuition in photonics characterisation, and spatial data management techniques, and will undertake a 3 month secondment at NNL’s Workington Lab, where they will deploy the new techniques, and which they will use as a base to explore underground locations in the north of England, working with existing SMEs such as VRGS Ltd, and operators of underground locations such as Honister Slate Mine.
The PhD starting in October 2021 is funded by an iCASE award through support from EPSRC and the National Nuclear Laboratory. This is a 4-year studentship that will cover all tuition fees for the duration of the PhD and provide a tax-free stipend to cover living costs (exact amount to be confirmed). The funding will cover travel and related costs linked to the research project. Applicants must meet the criteria for UKRI-funded studentships.
For further information about the project or any informal enquiries, please contact Professor Philip Martin ([email protected]). Please contact the admissions team at [email protected] with any queries you may have regarding the application process or funding.