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Department of Computer Science


Programmable Mixed-Signal Fabric for Machine Learning Applications

Primary supervisor

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Other projects with the same supervisor

Funding

  • Competition Funded Project (Students Worldwide)

This research project is one of a number of projects at this institution. It is in competition for funding with one or more of these projects. Usually the project which receives the best applicant will be awarded the funding. Applications for this project are welcome from suitably qualified candidates worldwide. Funding may only be available to a limited set of nationalities and you should read the full department and project details for further information.

Project description

In the EPSRC funded project FORTE, we are examining analogue, digital and mixed-signal reconfiguration enabled by memristive materials. In this PhD project, we will design a processing element that can operate in digital and analogue mode and that can be integrated into a larger fabric. Memristors can be used as re-programmable analogue and digital memories. The goal of this project is to use this capability for machine learning applications that normally benefit from large on-chip weight storage and where analogue processing is often very feasible. Throughout this project, we will produce a test chip for some processing elements as well as a final larger machine learning acceleration chip. In order to map applications to the planned chip, the architecture will be tailored to be compatible with established machine learning frameworks (e.g., TensorFlow or Caffe). The core of this project is on network inference, but training maybe possible as well.

The candidate should have a first class or upper second class honours degree, or a master???s degree (or equivalent qualification), in Computer Science or Electronic Engineering. Evidence of good spoken and written English has to proven with an IELTS score (or equivalent) of 6.5 or above for students whose first language is not English and who have no degree from an English speaking university. This position is open to all qualified candidates irrespective of nationality. The ideal candidate for this project should have some background in hardware and/or FPGA design as well as experience in using a machine learning framework.

A scholarship for this project is available as one of a number of projects at this institution. This is in competition for funding with one or more of our projects. Usually the projects which receives the best applicants will be awarded the scholarship. Early applications for this project are welcome from suitably qualified candidates worldwide. Funding may only be available to a limited set of nationalities and you should read the full department and project details for further information.

Person specification

For information

Essential

Applicants will be required to evidence the following skills and qualifications.

  • You must be capable of performing at a very high level.
  • You must have a self-driven interest in uncovering and solving unknown problems and be able to work hard and creatively without constant supervision.

Desirable

Applicants will be required to evidence the following skills and qualifications.

  • You will have good time management.
  • You will possess determination (which is often more important than qualifications) although you'll need a good amount of both.

General

Applicants will be required to address the following.

  • Comment on your transcript/predicted degree marks, outlining both strong and weak points.
  • Discuss your final year Undergraduate project work - and if appropriate your MSc project work.
  • How well does your previous study prepare you for undertaking Postgraduate Research?
  • Why do you believe you are suitable for doing Postgraduate Research?