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Oxide memristor devices for sensors with machine learning capabilities

   School of Science

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  Dr P Borisov, Prof S Saveliev  No more applications being accepted  Funded PhD Project (Students Worldwide)

About the Project

It is possible to run machine learning algorithms to classify and predict time-dependent input signals from sensors in application areas such as language processing, environmental, engineering, or medical monitoring. However, high energy consumption associated with the state-of-the-art hardware for neural networks is hindering development of mobile, compact sensors that can be operated stand-alone and offline. This is an opportunity to design devices that use fundamentally new physical approaches to processing neural networks in order to tackle this issue.

Loughborough University is a top-ten rated university in England for research intensity (REF, 2014) and an outstanding 66% of the work of Loughborough’s academic staff who were eligible to be submitted to the REF was judged as ‘world-leading’ or ‘internationally excellent’, compared to a national average figure of 43%.

In choosing Loughborough for your research, you’ll work alongside academics who are leaders in their field. You will benefit from comprehensive support and guidance from our Doctoral College, including tailored careers advice, to help you succeed in your research and future career. Find out more.


The goal of this project is experimental development of thin film devices capable of processing time-dependent electrical signals as part of a neural network. You will prepare thin films of oxide materials; employ different characterisation techniques to study the material properties; design and build novel electronic devices; test their performance with respect to the industry standard benchmarks.

This research project is at the intersection of artificial intelligence and device physics, and involves collaborative work between academic researchers in Physics, Chemistry, Computer Science and our industrial partner ARM Ltd. You will work closely with the supervisors and participate in weekly meetings with a large team of other academics, research staff and PhD students at Loughborough linked to the recently funded EPSRC grants EP/T027479/1 and EP/S032843/1.

Find out more:

Please contact Dr Pavel Borisov, [Email Address Removed] for further information about the project.

Entry requirements for United Kingdom

Applicants should have, or expect to achieve, at least a 2:1 Honours degree (or equivalent) in Physics, Material Science or Engineering or a related subject. A relevant Master’s degree and experience in one or more of the following will be an advantage: first-hand working experience with thin film preparation and characterisation techniques, neural networks, memristors. We would particularly welcome applicants who are good at working as part of a team and interested in cross-disciplinary collaborations.

Please see the programme website for international entry requirements by country.

English language requirements

Applicants must meet the minimum English language requirements. Further details are available on the International website.


All applications should be made online at Under programme name, select ‘Physics’

Please quote reference number: PB/PH/2021

Funding Notes

Please note that studentships will be awarded on a competitive basis to applicants who have applied to this project and other advertised projects within the School. Funding decisions will not be confirmed until early 2022. The studentship is for three years and provides a tax-free stipend of £15,609 per annum for the duration of the studentship plus tuition fees at the UK rate. International (including EU) students may apply however the total value of the studentship will cover the International Tuition Fee Only.
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