The Department of Chemical Engineering at the University of Bath is inviting applications for the following fully funded ο»ΏPhD project/studentship, expected to commence late October or November 2025. An alternative start date may be possible for the right candidate.
This advert may close early if a suitable candidate is identified. Early application is therefore encouraged.
Project
Although nuclear power provides 10% of global electricity (Reference 1) and is viewed as a key technology during transition to a fully decarbonised energy sector, end-of-life decommissioning of nuclear power plants and nuclear processing sites remains a key challenge. The inherent dangers and challenges in working with nuclear material mean that the development of new treatment and abatement technologies is heavily reliant on accurate modelling approaches. The prediction of, for example, thermodynamic data and phase behaviour of the radionuclides involved, and their interaction with other components present in the various waste streams is an essential component of those models, but is an area which is currently underexplored.
In this project, you will work alongside experts in molecular simulation and from the nuclear industry to develop multiscale models capable of describing the interplay between key radionuclides and the mineral surfaces present in waste storage and processing sites. You will employ a range of modelling techniques, including density functional theory, Monte Carlo simulations, and molecular dynamics simulations, and explore the use of machine learning or other AI-driven approaches to link and accelerate different modelling techniques.
Ultimately, this project will help drive progress in key decommissioning challenges, with a particular focus on waste treatment from the Magnox Swarf Storage Silos (Reference 2). In addition to support from the supervisory team at Bath, you will benefit from industrial supervision and support from the UK National Nuclear Laboratory (UKNNL) and Sellafield Ltd. You will also join the Centre for Integrated Materials, Processes and Structures at Bath, benefiting from support and mentoring from a network of world-leading researchers. This PhD opportunity offers an optional, fully funded 3 months industrial placement at a UKNNL site.
Candidate Requirements
You will have a strong background in chemical engineering, chemistry, physics or a related field. Previous experience in computational chemistry or molecular simulation is not essential.
Applicants should hold, or expect to receive, a First Class or high Upper Second Class Honours degree (or the equivalent). A masterβs level qualification would also be advantageous.
Non-UK applicants must meet our English language entry requirement.
Enquiries and Applications
Informal enquiries are welcomed and should be directed to Dr Lennox - m.j.lennox@bath.ac.uk
Formal applications must be submitted via this link: https://samis.bath.ac.uk/urd/sits.urd/run/siw_ipp_lgn.login?process=siw_ipp_app&code1=RDUCE-FP01&code2=0020
You must select 'EPSRC DTP' from the dropdown menu in the 'Funding your studies' section of the application form and provide the supervisor's name and project title in the 'Your PhD project' section. Failure to complete these steps will result in a delay to the processing of your application and may cause you to miss the deadline.
More information about applying for a PhD at Bath may be found on our website.
Equality, Diversity and Inclusion
We value a diverse research environment and aim to be an inclusive university, where difference is celebrated and respected.Β We welcome and encourage applications from under-represented groups.
If you have circumstances that you feel we should be aware of that have affected your educational attainment, then please feel free to tell us about it in your application form. The best way to do this is a short paragraph at the end of your personal statement.
Keywords
Energy sector, energy security, nuclear decommissioning, nuclear safety, waste treatment, computational chemistry, molecular simulation, radionuclides sorption, atomic scale modelling, thermodynamics.