Research Fellow in Embedded Control for Autonomous Vehicles
Applications are invited for a postdoctoral research fellowship, working on an exciting collaborative project on high performance autonomous vehicles. The project is funded by Innovate UK and is being undertaken with partners from the automotive and motorsport industry. The project will involve the development, implementation and testing of novel motion planning and control algorithms for autonomous vehicles able to optimally interact with onboard active chassis control systems during high acceleration manoeuvring.
Organisation Cranfield University
School/Department School of Aerospace, Transport and Manufacturing
Based at Cranfield Campus, Cranfield, Bedfordshire
Hours of work 37 hours per week, normally worked Monday to Friday
Contract type Fixed term contract
Fixed Term Period Until 31 May 2020
Salary £32,094 per annum
Apply by 21/06/2018
Cranfield is an exclusively postgraduate university that is a global leader for education and transformational research in technology and management. The Advanced Vehicle Engineering Centre (AVEC) has a worldwide reputation for excellence in teaching and research in automotive engineering, mechatronics and motorsport. The Centre offers four taught MSc courses, a PhD research programme and a range of continuing professional development courses. It also conducts industry-focused research and consultancy for clients throughout the automotive industry including (but not limited to) Vehicle OEMs, Tier 1 suppliers, R&D centres, universities, engineering firms and consultancies.
AVEC has recently secured significant funding for a wide range of advanced vehicle related engineering research programmes. Our on road and off road capabilities are underpinned by sector leading, state-of-the-art facilities in which the University and its partners have invested heavily. This infrastructure includes our new Intelligent Mobility Engineering Centre (IMEC) with specialist laboratories for mechatronics, battery development, hardware in the loop (HIL) and simulation, the Multi-User Environment for Autonomous Vehicle Innovation (MUEAVI) facility with its 'Intelligent Road' and our Off Road Dynamics and Vehicle Structures unit.
Applications are invited for a postdoctoral research fellowship, working on an exciting collaborative project on high performance autonomous vehicles. The project is funded by Innovate UK and is being undertaken with partners from the automotive and motorsport industry. The project will involve the development, implementation and testing of novel motion planning and control algorithms for autonomous vehicles able to optimally interact with onboard active chassis control systems during high acceleration manoeuvring. The completed algorithms will be implemented and tested in a prototype vehicle, developed by our industrial partners. The research fellow will focus on the development of the embedded control system for the autonomous vehicle and the implementation of advanced motion planning and control algorithms. The post holder will work closely with our industrial and research partners and will be expected to help mentor PhD and MSc students working in the group.
Applicants must hold a PhD (or close to completion) in mechanical, electrical & electronic engineering, control engineering, robotics or computer science or other relevant discipline - or be close to completion. Experience of embedded control systems, real-time systems, real time control implementation and instrumentation, in particular in automotive or robotics applications is essential. Experience in autonomous vehicle motion planning and control and/or vehicle dynamics and active chassis control, would be advantageous.
For an informal discussion, please contact Dr Stefano Longo, Senior Lecturer in Vehicle Control and Optimisation on (E); firstname.lastname@example.org.
At Cranfield we value Diversity and Inclusion, and aim to create and maintain a culture in which everyone can work and study together harmoniously with dignity and respect and realise their full potential.