The University of Surrey is pleased to announce an exciting PhD studentship opportunity focused on cutting-edge research that combines chemometrics, artificial intelligence (AI), and data analytics to improve the characterisation of materials during nuclear site decommissioning. This interdisciplinary project, developed in close collaboration with the Nuclear Decommissioning Authority (NDA) and NRS Dounreay, aims to transform the way radiological and chemical contamination are detected and analysed.
Project Overview
Decommissioning of nuclear sites presents complex challenges in accurately assessing contamination and activity levels. This PhD project addresses these challenges by developing a novel data analytics platform for spectroscopic data. The platform will integrate:
Advanced multivariate curve resolution methods
Physics-informed AI models
Preprocessing and statistical tools tailored for nuclear site data
Uncertainty quantification to ensure interpretability and robustness
Unlike traditional “out-of-the-box” machine learning algorithms, this approach prioritises physical interpretability, noise reduction, and accurate uncertainty measurement, offering a more reliable solution for the NDA’s data analysis needs.
Training and Research Environment
The selected candidate will work in a vibrant, supportive, and interdisciplinary research environment within the School of Chemistry and Chemical Engineering at the University of Surrey. The project offers:
Advanced training in AI, data science, and computational chemistry
Hands-on research collaboration with NDA and UK National Nuclear Laboratory (UKNNL)
Opportunities for international exposure and secondments at NDA facilities
Development of soft skills and professional networks for a successful research career
Supervision Team
The project will be co-supervised by:
Dr Michael Short
Dr Monica Felipe-Sotelo
Dr Carol Crean
Dr Jeremy Andrew (NRS Dounreay)
This supervisory team brings together extensive expertise in computational chemistry, data science, and nuclear research.
Eligibility Criteria
This opportunity is open to UK nationals only.
Applicants should hold either:
A first-class or upper second-class honours degree in a relevant subject (or an equivalent overseas qualification), or
A lower second-class degree with a strong Master’s degree (typically distinction-level).
Relevant disciplines include:
Chemical Engineering
Chemistry
Computer Science
Mathematics
Other science or engineering fields with strong computational content
Essential skills include some coding experience in languages such as Python, MATLAB, or Julia.
The ideal candidate will demonstrate:
Enthusiasm for interdisciplinary research
Ability to work both independently and as part of a team
A commitment to inclusive, responsible research and innovation
International candidates must meet English language requirements, typically IELTS 6.5 overall with no less than 6.0 in each category.
How to Apply
Applications must be submitted via the Chemical and Process Engineering PhD programme page. Instead of a research proposal, upload a document stating:
The project title: AI-Enhanced Spectroscopic Data Analysis for Nuclear Decommissioning
The name of the primary supervisor: Dr Michael Short
Application Deadline: 06 July 2025
Contact Information
Dr Michael Short
Room: 03 BC 02
📞 +44 (0)1483 689864
📧 m.short@surrey.ac.uk
Research Group: Information and Process Systems Engineering
