Research Fellow in Vision Based Navigation for Planetary

Cranfield, Bedford
20 Dec 2017
End of advertisement period
19 Jan 2018
Contract Type
Fixed Term
Full Time

Research Fellow in Vision Based Navigation for Planetary  

   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   12 months
Salary  £32,094 to £35,773 per annum (with additional performance related pay up to £44,716 per annum)
Apply by   19/01/2018 

This post offers challenging and stimulating opportunities for researchers with a background in Vision based localisation for ground mobile robots. The work covers the development of an innovative thermal imaging based localization system to improve rover’s navigation in Mars. You will have the chance to work and technically manage activities of a prestigious project funded through a well-known competition at the UK governmental level on space applications. 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 Vision (Thermal) based localization for planetary rovers
  • 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). You will also have significant expertise in image processing and computer vision 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 for space or other autonomous vehicles, experience in vision based localization (SLAM) for autonomous vehicles, Multi modality data acquisition and fusion and Thermal imaging and LIDAR exposure are a plus.