Research Fellow in Autonomous Cars Guidance

Cranfield, Bedford
10 Jan 2018
End of advertisement period
08 Feb 2018
Contract Type
Fixed Term
Full Time

Research Fellow in Autonomous Cars Guidance 

Organisation    Cranfield University
School/Department    Centre for Electronic Warfare, Information and Cyber
Based at    Shrivenham, Oxfordshire - Cranfield Defence and Security 
Hours of work   37 hours per week
Contract type   Fixed term contract
Fixed Term Period   One year
Salary   £32,094 to £35,773 per annum with performance related pay up to £44,716 per annum
Apply by    08/02/2018 

Cranfield is an exclusively postgraduate university that is a global leader for education and transformational research in technology and management.
This post offers challenging and stimulating opportunities for researchers with a background in Guidance and Navigation for Autonomous cars. The work covers areas from the automatic perception using imaging sensors to the path planning and obstacle avoidance for autonomous cars. You will have the chance to work and technically manage activities of a prestigious funded project with the direct involvement of an industrial partner. Working on other industrially funded projects related to autonomous vehicles is also part of the duties of this post.

Signals and Autonomy Group is one of the six groups of Centre for Electronic Warfare, Information and Cyber. Internationally reputable, the Group covers a wide variety of topics encompassing; Vision based Navigation systems, Autonomous Vehicles, Security, Automatic Object Recognition, 2D/3D Mapping, and Guidance and Control Techniques.

Main responsibilities include: 

  • To perform research in Guidance and Navigation for Autonomous cars
  • To publish high quality journals based on the research completed
  • To manage the daily basis interaction with our research/industrial partners
  • To supervise practical work where it is part of the intended project or other projects in the Signal and Autonomy Group

You will have a PhD/doctorate (or nearing completion). Significant expertise in path planning techniques and obstacle detection/avoidance and/or navigation systems from industrial or academic exposure; a track record of publications in peer reviewed relevant conferences and journals and very good Matlab/C++ programming skills.

PhD with an application on computer vision or Guidance or decision-making or Control, Experience in autonomous cars research, Multi modality data acquisition and fusion and LIDAR and car’s dynamics exposure are a plus.