This PhD project at The University of Manchester, hosted by the Department of Computer Science and the International Centre for Neuromorphic Systems (ICNS), explores the computational principles underlying sensorimotor integration in neuromorphic systems. The research aims to unravel how the human brain transforms egocentric (self-centred) spatial information into allocentric (environment-centred) representations, a process fundamental to natural navigation and interaction with complex environments.

The project is structured around two main pillars: theoretical investigation and practical application. The theoretical component focuses on modelling egocentric-to-allocentric visuomotor transformations using neuromorphic cameras, integrating tactile information and motor control. This involves deep learning, mathematical modelling, and neuromorphic computing—a brain-inspired approach that designs hardware and software mimicking biological neural processes. Neuromorphic devices provide power-efficient, embedded, and low-latency event-based platforms ideal for real-time sensory processing.

The practical aspect involves developing applications that leverage neuromorphic systems, such as event-based cameras and tactile sensors. These applications target challenges in robotic navigation, brain-machine interfaces, and supernumerary robotic limbs, requiring robust and adaptive systems capable of integrating visual and tactile data with motor control. The project offers access to state-of-the-art neuromorphic devices, GPUs, and a vibrant research community with expertise in embedded systems, neuromorphic hardware, and advanced algorithms.

Applicants should possess a strong academic background in Computational Neuroscience, Computer Science, Electrical Engineering, Physics, or related disciplines. Essential skills include programming (Python, C/C++), machine learning, and deep learning. Experience in brain-machine interfaces and neuroscience is highly desirable. Candidates must demonstrate excellent analytical and problem-solving abilities. Eligibility requires at least a 2.1 honours degree or a master’s (or international equivalent) in a relevant field. English language certification may be required for non-native speakers.

Funding is available for excellent candidates through competence-based faculty funding, covering tuition fees and providing a tax-free stipend at the UKRI rate (£20,780 for 2025/26), with annual increases expected. Self-funded students are also welcome to apply. The anticipated start date is October 2026, and applications are accepted year-round. Early application is recommended as the advert may be removed before the deadline.

To apply, candidates should submit an online application via the university portal, specifying the project title, supervisor, funding status, previous study details, and referee contacts. Required documents include transcripts, CV, a supporting statement outlining motivation and relevant experience, and an English language certificate if applicable. Contacting the supervisors prior to application is strongly encouraged to discuss suitability and motivation for the project.

The University of Manchester is committed to equality, diversity, and inclusion, welcoming applicants from all backgrounds and supporting flexible study arrangements. For further information, visit the project page or contact the admissions team at [email protected].