Application details:
Reference number: PB/PH/2022
Start date of studentship: 1st October 2022
Closing date of advert: 16th March 2022
Interview date:
Supervisors:
Primary supervisor: Dr Pavel Borisov
Secondary supervisor: Dr Sergey Saveliev
Short Introductory Paragraph
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 (REF2014). In choosing Loughborough for your research, you will work alongside academics who are leaders in their field. You will benefit from comprehensive support and guidance from our Graduate School, including tailored careers advice, to help you succeed in your research and future career.
Find out more: http://www.lboro.ac.uk/study/postgraduate/supporting-you/research/
Full Project Detail:
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:
https://www.lboro.ac.uk/departments/physics/staff/academic/pavel-borisov/
Please contact Dr Pavel Borisov, [email protected] for further information about the project.
Entry requirements:
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.
Funding information:
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 3 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.
Contact details:
Name: Dr Pavel Borisov
Email address: [email protected]
Telephone number: +44 (0)1509 228260
How to apply:
All applications should be made online at http://www.lboro.ac.uk/study/apply/research/ . Under programme name, select ‘Physics’
Please quote reference number: PB/PH/2021