Machine Learning and mmWave Radar Engineer


The Role

Your new career starts here with Plextek

Details

  • Location Plextek, CB10 1NY
  • Position Machine Learning and mmWave Radar Engineer (KTP Associate)
  • Placement FTC 30 months

About the position

Location: Plextek, Great Chesterford, near Cambridge, UK

An exciting opportunity to work as a Knowledge Transfer Partnership (KTP) Associate has arisen as part of a collaboration project between Plextek Services Limited and Cranfield University.

The aim of the KTP project is to develop a low size, weight, power (SWaP) and cost millimeter-wave radar sensor, augmented by the latest generation of Machine Learning (ML) algorithms, to enable autonomous systems to navigate accurately and safely in industrial settings.

KTPs are the UK’s oldest knowledge transfer programme, supporting partnerships between business and universities or research organisations, placing talented graduates (KTP Associates) to work on innovative, high-profile projects. KTPs are part grant-funded by Innovate UK, the United Kingdom’s innovation agency, which provides money and support to organisations to make new products and services on behalf of the UK Government.

About the Role

You will enhance the capability of Plextek’s credit-card sized millimeter-wave radars, developed in-house, through embedding modern Machine Learning (ML) algorithms to provide autonomous systems with an enhanced picture of the environment. Your duties will include:

  • Identify and implement a set of ML algorithms to enhance performance of Plextek’s mm-wave radar technology and outperform competing technology
  • Conduct detailed experiments to assess performance and produce data to market the capability
  • Create a real-time proof-of-concept system as the basis of a marketable demonstrator to showcase to prospective clients

You will be based at Plextek, near Cambridge, and will work closely with John Markow (Vice President of Innovation at Plextek), Dr Aled Catherall (CTO of Plextek) and Prof. Alessio Balleri, (Professor of Radar Systems at Cranfield University), in addition to engineers at Plextek and team of academics and researchers from the Centre for Electronic Warfare, Information and Cyber at Cranfield University in Shrivenham.

About You

You will have a strong honours degree (minimum of a 2.1) in Electrical & Electronic Engineering, Computer Science, Physics or closely related disciplines, together with experience in quantitative research, Radio Frequency (RF) sensing and Machine learning (ML). You will have the ability to communicate complex information clearly, excellent project and time management skills, and excellent oral and written communication and presentation skills.

Excellent team-working and inter-personal skills are also essential for this role.

This role would suit an individual with excellent technical skills and the ability to code proficiently in Matlab (for off-line data processing) and Python or C (to enable real time operations).

In return you will receive extensive practical and formal training, gain marketable skills, broaden your knowledge and expertise within an industrially relevant project, and gain valuable experience from industrial and academic mentors. You will benefit from a Personal Development Budget of £5,000.

About Cranfield University

As a specialist postgraduate university, Cranfield’s world-class expertise, large-scale facilities and unrivalled industry partnerships are creating leaders in technology and management globally. Learn more about Cranfield and their unique impact here.

Based just south of Cambridge, Plextek provides unique solutions for our customers by solving today’s hardest engineering problems. Our customers span a broad range of markets including healthcare, industrial, defence, security and transport. You can find out more about us here.

How to apply                                   

For an informal discussion about this opportunity, please contact Professor Alessio Balleri at a.balleri@cranfield.ac.uk.

This partnership received financial support from the Knowledge Transfer Partnerships (KTP) programme. KTP aims to help businesses to improve their competitiveness and productivity through the better use of knowledge, technology and skills that reside within the UK knowledge base. This successful Knowledge Transfer Partnership project, funded by UK Research and Innovation through Innovate UK, is part of the government’s Industrial Strategy.

You can view this role on the Cranfield University website here. 

Details

  • Location Plextek, CB10 1NY
  • Position Machine Learning and mmWave Radar Engineer (KTP Associate)
  • Placement FTC 30 months

Apply for the role

You can apply for this role directly with Cranfield University, using the link at the bottom of this page.