Research Assistant/Associate at Newcastle University

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Company description:

We are a world class research-intensive university. We deliver teaching and learning of the highest quality. We play a leading role in economic, social and cultural development of the North East of England. Attracting and retaining high-calibre people is fundamental to our continued success.

Job description:

The Role

The Microsystems Research Group is looking for a motivated Research Assistant/Associate to support the School of Engineering’s EPSRC project “UKRI-RCN: Exploiting the dynamics of self-timed machine learning hardware (ESTEEM)”.

The Microsystems Group is prominent in the UK. It has an international reputation for world-leading research across microelectronics design and computer systems engineering with ten academic members, 10+ Research Assistants/Associates and 30+ PhD students.

This project will investigate opportunities for improving performance and energy efficiency in artificial intelligence hardware created by the inherent time and power elasticity of self-timed circuits. The project will lay foundation to a new design methodology for building electronic devices and systems with machine learning (ML) capabilities at the micro- and nano-scale granularity. Those devices will be widely leveraged in many at-the-edge applications such as environmental sensors, traffic monitors, wearables, as well potential commodity ML-enhanced devices that can be used as building blocks in computer systems of the future. The project outcomes in theory and design methodology will be validated by means of extensive simulations, prototyping, IC fabrication and testing, and, ultimately, via an embodiment of the new hardware solutions into a concrete Internet of Things (IoT) application. A particularly challenging and breaking through validation will be the development and fabrication of the first asynchronous machine learning integrated circuit using flexible substrates.

Within the project, the nominated candidate will work on both aspects, the machine learning hardware, both training and inference, and self-timed IC design and test.

The nominated candidate will perform tasks under the guidance of the Principal Investigator and three Co-Investigators, work closely with a multidisciplinary team, external academic partners and industrial partners (PragmatIC, Cambridge Future Tech).

To find out more about the School of Engineering click here

To find out more about the Faculty of Science, Agriculture and Engineering 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 further information including the essential and desirable criteria or to apply, click the ‘Apply’ button above.

For informal enquires please contact Professor Alex Yakovlev al***********@ne*******.uk

Key Accountabilities

  • Utilise Asynchronous design methods, Electronic Design Automation tools, Machine learning models for designing energy efficient and low latency AI hardware in at-the-edge applications
  • Work on the different tasks in the research project to generate deliverables in a timely manner and meet the project objectives
  • Provide active intellectual contributions to the research project by ways of, e.g., planning for implementation, generating new ideas, interacting with industrial partners and conducting lab experiments
  • Prepare clear, well-written reports and draft scientific papers to meet the requirements of high-impact journals on time according to the project timeline set out by the Investigators team
  • Present research findings at conferences or through publications in reputable outlets appropriate to the discipline


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