Event based signal processing for isotope identification at reduced power

Conventional detection systems typically comprise analogue sensors, analogue to digital conversion, digital signal processing and sometimes digital to analogue conversion, all driven by a synchronous clock. Such systems continuously consume power even in environments where sensor signals may be rare.  Conventional computing does not exploit the opportunities for parallel event processing which may offer significant power savings.

This fully funded project proposes to reconfigure the “sensor to result” system chain to make it asynchronous and entirely event driven. Event based processors only consume significant power where events arrive rather than in response to a continuous clock signal. In this fundamental  research program, we aim to develop understanding and demonstrate early prototypes of the event processing chain: the conversion of analogue sensor data into asynchronous event data, the use of asynchronous analogue and or digital processors, and the conversion of event signals back into the analogue domain. Solutions may include both conventional signal processing adapted to the asynchronous environment and neuromorphic processors in the event domain.

Our approach will involve the study of a commercial application with our industrial and academic partners.

The project contains a UK based industrial partner, the University of Edinburgh and two other major UK universities.

Closing Date: 

Friday, January 31, 2020

Principal Supervisor: 


Minimum entry qualification - an Honours degree at 2:1 or above (or International equivalent) in a relevant science or engineering discipline, possibly supported by an MSc Degree. Further information on English language requirements for EU/Overseas applicants.


Tuition Fees and Stipend are available for Home/EU students only.

Further information and other funding options.