Neuromorphic Phase-Change Computing - Engineering - EPSRC DTP funded PhD Studentship Ref: 2929

About the award

This project is one of a number funded by the Engineering and Physical Sciences Research Council (EPSRC) Doctoral Training Partnership to commence in September 2018. This project is in direct competition with others for funding; the projects which receive the best applicants will be awarded the funding.

The studentships will provide funding for a stipend which is currently £14,553 per annum for 2017-2018. It will provide research costs and UK/EU tuition fees at Research Council UK rates for 42 months (3.5 years) for full-time students, pro rata for part-time students.

Please note that of the total number of projects within the competition, up to 15 studentships will be filled.

Supervisors
Professor C David Wright, University of Exeter
Professor Harish Bhaskaran
, University of Oxford

Location 
Streatham Campus, Exeter

Project Description
This project aims to develop a new wave of industry-relevant technologies that will extend the limits facing mainstream computing architectures.

We will do this by developing innovative nanoelectronic and nanophotonic phase-change devices and systems that fuse together the core computational tasks of information processing and data storage (memory). Our novel phase-change based hardware will have the ability to learn, adapt and evolve. We will also aim to take advantage of the huge benefits (in terms of increases in speed/bandwidth and reduction in power consumption) which can be gained from performing key functions in the photonic rather than the electronic domain.  

Our basic information processing building blocks will draw inspiration from biological approaches, providing computing primitives that can mimic the essential features of brain-like synapses and neurons to deliver a new foundation for fast, low-power computing based around non-von Neumann approaches. We will combine such computing primitives into reconfigurable integrated processing networks that can implement in hardware novel, intelligent, self-learning and adaptive computational approaches - including spiking neural networks, computing-in-memory and autonomous reservoir computing – and that are capable of addressing complex real-world computational problems in fast, energy-efficient ways.

The work carried out in the project will be of extremely high relevance in terms of future computing imperatives, such as the analysis and exploitation of ‘big data’ and the ubiquity of computing arising from the ‘Internet of Things’. Work will be carried out in collaboration with a number of EPSRC and industrial researchers including colleagues at the Universities of Oxford, Southampton, Münster and Pennsylvania, as well as the cognitive computing team at IBM Zurich.

Entry Requirements
You should have or expect to achieve at least a 2:1 Honours degree, or equivalent, in Physics, Electronic Engineering, Materials Science or related subjects.
Experience in electronic and/or photonic materials and devices, microfabrication, neuromorphic computing (neural networks etc.) is desirable, though not essential.

If English is not your first language you will need to meet the English language requirements and provide proof of proficiency. Click here for more information and a list of acceptable alternative tests

The majority of the studentships are available for applicants who are ordinarily resident in the UK and are classed as UK/EU for tuition fee purposes.  If you have not resided in the UK for at least 3 years prior to the start of the studentship, you are not eligible for a maintenance allowance so you would need an alternative source of funding for living costs. To be eligible for fees-only funding you must be ordinarily resident in a member state of the EU.  For information on EPSRC residency criteria click here.

Applicants who are classed as International for tuition fee purposes are NOT eligible for funding. International students interested in studying at the University of Exeter should search our funding database for alternative options.

Summary

Application deadline:10th January 2018
Value:3.5 year studentship: UK/EU tuition fees and an annual maintenance allowance at current Research Council rate. Current rate of £14,553 per year.
Duration of award:per year
Contact: Doctoral Collegepgrenquiries@exeter.ac.uk

How to apply

You will be required to upload the following documents:
•       CV
•       Letter of application outlining your academic interests, prior research experience and reasons for wishing to
        undertake the project.
•       Transcript(s) giving full details of subjects studied and grades/marks obtained.  This should be an interim
        transcript if you are still studying.
•       If you are not a national of a majority English-speaking country you will need to submit evidence of your current
        proficiency in English.  For further details of the University’s English language requirements please see
        http://www.exeter.ac.uk/postgraduate/apply/english/.

The closing date for applications is midnight (GMT) on Wednesday 10 January 2018.  Interviews will be held at the University of Exeter in late February 2018.

If you have any general enquiries about the application process please email: pgrenquiries@exeter.ac.uk.
Project-specific queries should be directed to the supervisor.

During the application process, the University may need to make certain disclosures of your personal data to third parties to be able to administer your application, carry out interviews and select candidates.  These are not limited to, but may include disclosures to:

• the selection panel and/or management board or equivalent of the relevant programme, which is likely to include staff from one or more other HEIs;
• administrative staff at one or more other HEIs participating in the relevant programme.

Such disclosures will always be kept to the minimum amount of personal data required for the specific purpose. Your sensitive personal data (relating to disability and race/ethnicity) will not be disclosed without your explicit consent.