Current modelling and simulations require either generic assumptions to be made for fluid dynamic based modelling leading to inaccuracies between modelled and experimental data or, intense computational recourses for limited duration yet highly accurate particle-in-cell (PIC) modelling. Kingston University has developed a simulation model, dubbed PERSEUS, that narrows the gap between these two simulation regimes by harnessing and advancing the latest developments in AI Machine Learning. This studentship is a continuation of prior work that is looking at using new cutting-edge deep learning models that have been developed in-house based on the OSIRIS Particle-In-Cell simulation software. The code needs to be verified and further developed with user cases against experimentally gathered data sets. The aim of this project is to collect data from plasma and combustion-based propulsion systems and analyses the effectiveness of PERSEUS for the space launch and propulsion sectors and wider aerospace industry.
The project supports Pulsar’s strategic roadmap in developing both chemical propulsion systems for launch and high-power electric propulsion systems for last mile delivery activities for spacecraft and upper stage launch systems. Simulation and test campaigns can be significantly costly in both time and cost having significant implications to technology hardware development. A software that allows for inspection of both micro and macro process accurately, that compiles faster than standard industry codes but delivers particle-in-cell accuracy has the potential to be a step-change technology. Verifying this against real world scenarios and processes is a key milestone in the further development of this code for industrial application.
This PhD covers a wide range of skills and so it is essential the candidate has a 2:1 or above degree in computing or aerospace/space technology engineering and can demonstrate through other projects or experiences knowledge across the disciplines of software development, plasma-based space propulsion systems, an interest in rocketry and chemical propulsion combustion and/or a deep understanding of machine learning theory and application. Expert tuition from academics across these areas will assist you during your PhD but it is important to demonstrate prior experience in your application.
This PhD studentship is part of the Rocketry Research, Teaching, and Training (R2T2) program and is an integrated doctoral programme, run across eight UK universities, which seeks to provide the opportunity to pursue a PhD in space launch technologies. Please see r2t2.org.uk for more details
For further details and to discuss a prospective application, please contact:
Dr Peter Shaw, p.shaw@kingston.ac.uk
Eligibility: Minimum Upper Second Honours degree in Engineering or Computer Sciences or a related discipline; a Masters degree in these subjects would be of advantage. In addition, applicants should be able to demonstrate an interest in Engineering and Computer Sciences (even if they only completed a degree in one of those areas) and an interest in space and launch propulsion and application of machine learning in software simulations.
Start date: 1 October 2025, 4 years full-time
Interviews: online on 15 July 2025
For information about what documentation is required with the application, see the project information on Findauniversity.com.
UK tuition fee plus stipend of £21,570 per year x 4 years
