Modelling memristive artificial neurons

Does the brain operate as a computer? In short the answer is no, but why? We use logic when thinking and coming to a decision by linking events in a causal relationship. Nevertheless, the human memory is much more distributed (pattern like) in contrast to localised computer bit-memory, has time decay (clogging) and is designed to process information pulse sequences (information/excitation waves) rather than operating with bits in different memory locations as a computer does. To mimic or emulate brain-like computations or neuromorphic computing, the new generation of memory elements should be developed. One of the most promising memory devices for neuromorphic computations and signal processing is a memristor, in which resistance switches between two states depending on applied electric pulse sequence (an information wave).

Using Loughborough’s expertise in solid state, thin films and modelling, in synergy with world leading centres of memristor research (HP Enterprise Labs and the University of Massachusetts Amherst) we intend to design, simulate, fabricate and produce prototypes of nanodevices where electric signals (information waves) can propagate, mimicking visual cortex functions for the next generation of brain-like neuromorphic chipsets for video and image analysis.
Loughborough neuromorphic team led by Prof. Saveliev, conducts the research in collaboration with the world leading research centres and industry, including the University of Massachusetts Amherst, The Salk Institute for Biological Studies (USA), ARM.

Entry requirements
- Applicants should have, or expect to achieve, at least a 2:1 Honours degree (or equivalent) in Physics or Mathematics
- A relevant Master's degree and / or experience in one or more of the following will be an advantage: Physics or Mathematics

How to apply
All applications should be made online. Under programme name select School of Science. Please quote reference number: PH/SS-Un1/2019