Machine Learning and mm Wave Radar Engineer (KTP Associate)

Fixed Term Contract for 30 months

£35,000 to £50,000 per annum, dependent upon qualifications and experience, plus £5,000 personal development budget 

Location: Plextek, Great Chesterford, near Cambridge, UK

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. 

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 

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 here. 

How to apply                                     

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

To apply please click above 'Apply' Button. Please do not hesitate to contact us for further details at people.shrivenham@cranfield.ac.uk. Please quote reference number 4926. 

Closing date for receipt of applications: 30 September 2024

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