Machine Learning and mm Wave Radar Engineer (KTP Associate)

Role Description

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 Us

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 our unique impact .

Our Values and Commitments

Our shared, stated values help to define who we are and underpin everything we do: Ambition; Impact; Respect; and Community. Find out more .

We aim to create and maintain a culture in which everyone can work and study together and realise their full potential. We are a Disability Confident Employer and proud members of the Stonewall Diversity Champions Programme. We are committed to actively exploring flexible working options for each role and have been ranked in the Top 30 family friendly employers in the UK by the charity . Find out more about our key commitments to Equality, Diversity and Inclusion and Flexible Working .

Working Arrangements

Collaborating and connecting are integral to so much of what we do. Our Working Arrangements Framework provides many staff with the opportunity to flexibly combine on-site and remote working, where job roles allow, balancing the needs of our community of staff, students, clients and partners.