Organisation
Cranfield University
Faculty or Department
Cranfield Defence and Security
Based at
Off Campus
Hours of work
37.5 hours per week, normally worked Monday to Friday
Contract type
Fixed term contract
Fixed Term Period
Fixed Term Contract for 30 months
Salary
£35,000 to £50,000 per annum, dependent upon qualifications and experience, plus £5,000 personal development budget
Posted Date
17/09/2024
Apply by
30/09/2024
Documents
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:
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 here.
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 here.
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 Working Families. Find out more about our key commitments to Equality, Diversity and Inclusion and Flexible Working here.
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.
How to apply
For an informal discussion about this opportunity, please contact Professor Alessio Balleri at [email protected].
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.