Sensor fusion enabled by photonic neuromorphic computing using phase-change materials

The use of functional materials that can “accumulate” information to carry out both memory and computing tasks in-situ is a growing field. Using optical integration onto silicon chips provides a unique opportunity to combine the benefits of silicon scaling and the wavelength multiplexing of optics onto a single platform. Within the Advanced Nanoscale Engineering Group we will significantly expand on our initial work on carrying out non-von Neumann computations (such as Vector-Matrix Multiplication directly in hardware) to a larger matrix to prove a lab scale demonstration of the potential for such hardware in defence-relevant computing tasks. Additionally we aim to benchmark such computations against existing state-of-the-art in terms of energy and operational speed.

This iCASE project, supported by Dstl, aims to build on this firm foundation of proven basic principles and develop phase-change-based computing primitives, specifically synapse and neuron mimics and (binary and multi-level) non-volatile memories and combine such primitives into non-von Neumann computing networks (architecture).  This work will be used to demonstrate proof-of-concept for defence-relevant computational tasks related to sensor processing and management.

This is a 4-year EPSRC Industrial CASE studentship in conjunction with Dstl and will provide full fees and maintenance for a student who has Home/Republic of Ireland or Islands fee status.  The stipend will be at least £17,285 per year.  Information on fee status can be found at

Candidates will be considered in the January 2021 admissions field which has an application deadline of 22 January 2021 and, if the studentship is unfilled, in the March 2021 admissions field which has an application deadline of 2 March 2021. 

Any questions concerning the project can be addressed to Professor Harish Bhaskaran (  General enquiries on how to apply can be made by email to  You must complete the standard Oxford University Application for Graduate Studies.  Further information and an electronic copy of the application form can be found at

Photonic Matrix Multiplication

Multiplication on a photonic chip


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