About the project
This project will develop a novel memristor device using nanoporous materials for the new generation of time and power efficient neuromorphic computing and AI.
The exponential growth of data digital communications and the advent of artificial intelligence has placed an urgent need for novel information technologies with huge storage capacity and efficient computing processing. The human brain is able to process and store information and to carry out complex functions such as perception, learning and memory using only a fraction of power than that of conventional computer. The key for such high energy efficiency in human brain lies in the fact that information can be both processed and stored within the synapses and neurons. Inspired by the functions of biological neurons and synapses in the brain, the memristor, a two-terminal switchable resistive memory, shows great potential to faithfully emulate the synaptic behaviour of human brain and become the main functional unit for energy-efficient neuromorphic computing circuitry.
This project will develop a two-terminal nanoporous materials (e.g. nanoporous silica) based memristor device for neuromorphic computing and AI. The unique control over the nanoporous material properties including pore size, density, orientation will provide a much needed platform to design novel memristors with different functionalities, better reliability, and high power-efficiency.
You will join the Sustainable electronic technologies research group (SET) in the School of Electronics and Computer Science (ECS). This is a dynamic research team with vast experience of neuromorphic memristor based neuromorphic computing and novel semiconductor material development.
You will also have access to advanced micro- and nanofabrication in the best University cleanroom facility in the UK as well as electronic characterization in our state-of-art measurement laboratory.
