Research Fellow

Full-time, fixed term to December 2027

The Computing Technologies research group of the Computing Technologies and Human Aspects research cluster is looking for a motivated Research Fellow to support the BEEC School’s EPSRC project “UKRI-RCN: Resource-aware Knowledge Transfer Methods for Machine Learning Hardware in At-the-Edge Applications (KNOT)”.

The Computing Technologies research group study a broad range of interdisciplinary research challenges covering various aspects of information and communication technologies in Cloud Computing, Big Data, AI and IoT application domains.

The project aims at developing low-cost resource-aware methods of knowledge transfer for machine learning hardware at controlled granularity to be used in heterogeneous at-the-edge applications. It will lay foundation to a new methodology for sharing knowledge between smart edge devices with a machine learning (ML) capability. The project outcomes in theory and design methods will be validated by means of extensive simulations, prototyping, and testing, and, ultimately, via an embodiment of the proposed solutions into a concrete IoT-scale application.

Within the project, the nominated candidate will work on both aspects, the machine learning software and hardware training, inference and transfer knowledge.

The nominated candidate will perform tasks under the guidance of the Principal Investigator, work closely with a multidisciplinary team, external academic partners (Newcastle University, University of Agder), and industrial partners (Literal Labs).

To find out more about the School of Built Environment, Engineering and Computing click here. To find out more about the LBU’s Computer science research and the Computing Technologies and Human Aspects research cluster click here.

We are committed to building and maintaining a fair and inclusive working environment and we would be happy to discuss arrangements for flexible and/or blended working. Additionally, the post is eligible for blended working between campus and home.

For informal enquires please contact:

Dr Anatoliy Gorbenko A.Gorbenko@leedsbeckett.ac.uk

Closing date: Friday 28th February 2025 (23:59)

For more information and to apply please click the 'Apply' button, above.

Working here means you’ll also have access to a wide range of benefits including our generous pension schemes, excellent holiday entitlements, flexible working, reduced study fees, subsidised fitness facilities and a lot more.

We welcome applications from all individuals and particularly from black and global majority candidates as members of these groups are currently under-represented at this level of post. All appointments will be based on merit

Advert information