Projects available for October 2024 

Applications are invited for the below projects.

Please ensure you have read our updated programme description before applying for projects.

Please check back for new projects. If you have contacted Dr Jonathan Tate about being added to our mailing list, you will be notified via email when new positions become available. If you wish to be added to our mailing list, please contact Jonathan at j.tate@imperial.ac.uk 

Due to the sensitive nature of the research being carried out, some projects may require you to be a UK national.

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Project title: A numerical-experimental investigation of Alloy 800H
Short project description: We aim to undertake a programme of work which explores the behaviour of Alloy 800H at two different length scales experimentally: meso-scale and macro-scale. This PhD project will deal with the lower length scale analysis that is required for informing meso-mechanical simulation work through experimental techniques such as high angular resolution electron back scatter diffraction and synchrotron X-ray diffraction. 
Supervisor(s): Dr Nicolo Grilli (UoB)
Institution:
University of Bristol
Further information:
Funded by EdF Energy.
Part-time: Not suitable for part-time study.
How to apply:
E-mail your CV and contact details for one academic reference to Dr Jonathan Tate (j.tate@imperial.ac.uk)
Deadline:
Ongoing until position is filled.

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Project title: Development of machine learning models for tungsten under extreme conditions
Short project description: This project aims to use machine learning techniques in estimating the behaviour of tungsten under extreme conditions. Tungsten, a pivotal plasma-facing material in nuclear fusion applications, stands resilient in the face of heavy irradiation and intense thermal environments. However, its mechanical behaviour under various service conditions imposed by a fusion reactor is difficult to test. Therefore, we invite passionate and forward-thinking researchers to contribute to the development of an accurate and
efficient material model using machine learning.

Supervisor(s):  Dr Burcu Tasdemir (UoB)
Institution:
University of Bristol
Further information:
Funded by United Kingdom Atomic Energy Authority (UKAEA).
Part-time: Enquire with supervisor.
How to apply:
E-mail your CV and contact details for one academic reference to Dr Jonathan Tate (j.tate@imperial.ac.uk)
Deadline:
Ongoing until position is filled.

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Project title: Effects of scattering models on LWR core analyses
Short project description:
The safety and operational performance of reactor cores relies on simulation tools which are used, with appropriate uncertainties, to set operating limits and determine operational practices on the nuclear fuel and the reactor core. Industry standard simulation tools generally use simplified representations of neutron angular scattering. In general, this approach is successful but would be expected to have limitations in areas of strong absorbers or abrupt changes in material properties such as the core-reflector interface. This project seeks to clarify the origins of errors associated with the existing approaches and outline what improvements could be expected from the use of more sophisticated scattering treatment models.
Supervisor(s):  Prof Eugene Shwageraus (Camb)
Institution:
University of Cambridge
Further information:
Co-funded by EdF Energy and iCASE award. Only candidates that are eligible for Home fees can be accepted.
Part-time: Enquire with supervisor.
How to apply: 
Direct application to Engineering Department, University of Cambridge. Ensure you nominate Prof Eugene Shwageraus as supervisor.
Deadline:
Ongoing until position is filled.

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Project title: Modelling of natural circulation flow in Pressurised Water Reactors
Short project description:
The aim is to develop computer aided geometric design (CAGD) compatible spatial discretisation methods for the Navier-Stokes equations (NSE) for use in coarse mesh computational fluid dynamics (CM-CFD) modelling of natural circulation/convection (NC) within the primary nuclear thermal-hydraulic circuit of nuclear reactors. The PhD student will develop CAGD-CFD high-order curvilinear virtual element (VE) spatial discretisation methods within the Nektar++ CFD modelling and simulation (M&S) framework.
Supervisor(s):
Prof Joaquim Peiro (ICL) and Dr Matt Eaton (ICL)
Institution:
Imperial College London
Further information:
Funded by Rolls-Royce Plc. Only UK nationals are invited to apply for this vacancy.
Part-time:
Not suitable for part-time study.
How to apply:
E-mail your CV and contact details for one academic reference to Dr Jonathan Tate (j.tate@imperial.ac.uk)
Deadline:
Ongoing until position is filled.

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Project title: Nuclear reactor physics burn-up-depletion algorithms
Short project description:
The advent of shared and distributed memory high performance computing (HPC) hardware architectures is driving innovations in nuclear reactor physics modelling and simulation software. The aim of this PhD is to develop appropriate shared and distributed memory parallel solution algorithms that are computational efficient for extremely large data sets and that can resolve each nuclear fuel burn-up/depletion time-step using a highly scalable approach.
Supervisor(s):
Dr Matt Eaton (ICL)
Institution:
Imperial College London
Further information:
Funded by Rolls-Royce Plc. Only UK nationals are invited to apply for this vacancy.
Part-time:
Not suitable for part-time study.
How to apply:
E-mail your CV and contact details for one academic reference to Dr Jonathan Tate (j.tate@imperial.ac.uk)
Deadline:
Ongoing until position is filled.

Project title: Optimising non-destructive testing frequency for integrity assessment
Short project description: 
NDE is currently used at intervals throughout the life of a component to detect if any cracks over a specified length have been formed. If a crack is found and its length measured, then the remaining useful life of the component can be 
estimated. The purpose of this PhD is to investigate (i) how uncertainties propagate through the process, (ii) how information obtained from NDE can be used to update crack growth model parameters to reduce uncertainty, (iii) the optimal inspection interval (which may not be constant) to achieve the most accurate outcome.
Supervisor(s):  
Dr Sergio Cantero Chinchilla (UoB)
Institution:
University of Bristol
Further information:
Funded by Rolls-Royce Plc
Part-time: Not suitable for part-time study.
How to apply:
E-mail your CV and contact details for one academic reference to Dr Jonathan Tate (j.tate@imperial.ac.uk)
Deadline:
Ongoing until position is filled.

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Project title: Quantifying uncertainty in the mechanical performance of fusion materials 
Short project description: 
Our vision is to design and assess the structural components critical for fusion plant using probabilistic analysis. To this end, the uncertainty in the predicted mechanical behaviour of components must be quantified so it can be used as an input parameter. Our proposed solution is to use physics-based simulations, calibrated via a limited number of targeted experiments, to accelerate and arguably improve uncertainty quantification for the performance of fusion materials. Our focus will be on the
mechanical behaviour of high-purity copper as a function of its microstructural features.
Supervisor(s):  
Prof Mahmoud Mostafavi (UoB)
Institution:
University of Bristol
Further information:
Funded by United Kingdom Atomic Energy Authority
Part-time: Enquire with supervisor.
How to apply:
E-mail your CV and contact details for one academic reference to Dr Jonathan Tate (j.tate@imperial.ac.uk)
Deadline:
Ongoing until position is filled.