Spiking neural networks (SNNs) represent a new generation of artificial neural networks (ANN), particularly well adapted to event-like data, such as events recorded by neuromorphic cameras or asynchronous streams of particle detection events (photons, neutrons,…). In contrast to more classical ANNs, SNNs are able to capture efficiently complex spatio-temporal patterns by adopting neural structures mimicking biological brains. However, important challenges still need to be addressed to accelerate the deployment of such networks to different applications, including efficient network design and training and appropriate hardware for fast and low-consumption implementation. In this PhD project, the student will investigate new statistical models and methods to train SNNs efficiently. A particular focus will be on probabilistic SNNs, which can benefit the Bayesian and variational inference formalisms for training. Possible applications investigated during the project include neuromorphic computing for computer vision tasks using event-cameras (for robotic and microscopy applications) and analysis of event streams for single-particle detectors such as arrays of single-photon avalanche diodes (SPADs), or neutron/gamma detectors.
How to Apply
1. Important Information before you Apply
When applying through the Heriot-Watt on-line system please ensure you provide the following information:
(a) in ‘Study Option’
You will need to select ‘Edinburgh’ and ‘Postgraduate Research’. ‘Programme’ presents you with a drop-down menu. Choose Chemistry PhD, Physics PhD, Chemical Engineering PhD, Mechanical Engineering PhD, Bio-science & Bio-Engineering PhD or Electrical PhD as appropriate and select September 2022 for study option (this can be updated at a later date if required)
(b) in ‘Research Project Information’
You will be provided with a free text box for details of your research project. Enter Title and Reference number of the project for which you are applying and also enter the potential supervisor’s name.
This information will greatly assist us in tracking your application.
Please note that once you have submitted your application, it will not be considered until you have uploaded your CV and transcripts.