security-critical systems. This project asks how far the output of an event camera can be trusted. The student will characterise how these sensors respond under demanding and adversarial conditions, assess what this means for downstream perception tasks such as detection and tracking, and investigate whether event-based sensing can support stronger guarantees about the data it produces. The work is experimental and hardware-oriented, combining laboratory measurement with signal processing and machine learning.
The project is supervised by a team spanning neuromorphic sensing and the security of cyber-physical systems. During the PhD, the student will gain experience in event-based vision, adversarial testing and security research. They will also gain experience in responsible disclosure and develop an understanding of the role of research ethics in security work. There are opportunities to engage with industry partners and to publish at leading international venues.
A background in cyber security, neuromorphic engineering, computer vision, robotics, electronic engineering or a related area is required. Experience with event cameras is desirable but not essential.
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 in a discipline directly relevant to the PhD Computer Science (or international equivalent). We can also accept any upper-second class (2:1) honours degree and a Master's degree at merit in a discipline directly relevant to the PhD Computer science (or international equivalent). A background in cyber security, neuromorphic engineering, computer vision, robotics, electronic engineering or a related area is required.
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.
