About the Project
Spacecraft operate in challenging environments where interactions between propulsion plumes, surfaces and particles can influence mission performance. During thruster operation or planetary landing, high-speed gas plumes can mobilize dust and particles, potentially causing surface erosion, contaminating sensitive optical components, and interfering with spacecraft systems. Understanding these rapidly evolving particle motions requires measurement techniques that can capture fast dynamics across…
a wide range of timescales.
This project will explore an emerging technology, neuromorphic/event-based imaging, to study plume–particle interactions relevant to spacecraft environments. Unlike conventional cameras that continuously record complete image frames, event cameras respond only to changes in light intensity at individual pixels. This enables very high temporal resolution while producing a sparse data stream, making the technology particularly attractive for observing fast-moving particles at a significantly reduced data rate.
The student will develop a laboratory-scale experiment in which a controlled gas jet is used to generate and mobilize particles, providing a safe and repeatable analog of plume-driven particle transport. An event camera will be used to capture particle motion, and computational methods will be developed to extract quantities such as particle trajectories, velocities, ejection angles and spatial dispersion. The performance of neuromorphic imaging will also be compared with conventional frame-based imaging to determine where event-based sensing offers advantages and where its limitations arise.
The project provides an opportunity to work at the intersection of spacecraft engineering, experimental fluid mechanics, optical diagnostics and emerging neuromorphic sensing technology. The student will gain hands-on experience with event cameras and experimental systems alongside training in image/event processing, particle tracking, MATLAB/Python programming, quantitative data analysis and uncertainty assessment.
By the end of the project, the student will have contributed to establishing the feasibility of a new measurement approach for spacecraft plume environments and generated preliminary experimental data that could support future research in areas including spacecraft propulsion, plume–surface interactions, planetary landing and lunar dust transport.
The project is particularly suitable for students interested in space engineering, experimental aerodynamics/fluid mechanics, imaging technologies, sensing, or experimental data processing. Prior experience with neuromorphic imaging is not required, relevant training will be provided during the project.
This project is expected to start in September 2027.
Before you apply: We strongly recommend that you contact the supervisors for this project before you apply.
How to apply: To be considered for this project you must complete a formal application through our online application portal. If you already have an applicant account this link will directly open an application for PhD School of Engineering Scholarships. If you don’t already have an applicant account, please follow the instructions here.
When applying, please specify the full title and supervisor/s of the project, details of your previous study, and names and contact details of two referees. You must also upload a Supporting Statement describing the motivation to apply to the project, your CV and transcripts of awarded and in-progress university qualifications. Please note late or incomplete applications will not be considered.
Equality, diversity and inclusion are fundamental to the success of The University of Manchester and central to all our activities. A diverse research community strengthens creativity, productivity and quality, while increasing the societal and economic impact of our work. We welcome applicants from all career paths, backgrounds and sections of the community, regardless of age, disability, ethnicity, gender, gender expression, sexual orientation or transgender status.
We welcome applications from candidates returning to study after a career break or experience in other roles. Flexible study arrangements may be available, including part-time study at 50%, 60% or 80%, subject to the requirements of the project and funder.
Eligibility: The standard academic entry requirement for this PhD is an upper second-class (2:1) honours degree (or international equivalent) in Mechanical/ Aerospace Engineering OR any upper-second class (2:1) honours degree and a Master’s degree at merit (or international equivalent) in Mechanical/ Aerospace Engineering.
Skills - Fluid Dynamics, Imaging, Data Processing skills in MATLAB/Python is desirable. Prior experience with neuromorphic imaging is not required, relevant training will be provided during the project.
This project will remain open until filled.
If your application is submitted by 1st November 2026, you can expect a decision by 18th December 2026.
If your application is submitted by 15th January 2027, you can expect a decision by 30th March 2027.
Self or externally funded students can also be considered for this project.
FSE_SoE
Funding Notes
Funding for this project covers tuition fees, UKRI minimum annual stipend (currently £21,805/annum) and up to a £2.5k/annum research training support grant for the full duration of the 3.5-year programme.