PhD Studentship - Computer Vision – Autonomous Road Vehicles Situational Awareness for Future Innovative Computing Group, School of Engineering and Computing Sciences Durham University, Durham, UK Supervisor: Dr Toby Breckon Award type: PhD Duration of award: 3.5 Years Applications are invited for a fully funded PhD student to work in the School of Engineering and Computing Science on the topic of developing a situational awareness framework for future autonomous road vehicles in collaboration with Jaguar Landrover (JLR) (http://www.jaguarlandrover.com/). This will include awareness and reaction to the behaviour of other dynamic scene entities, based on real-time scene understanding from on-board forward-facing stereo and additional on-board vehicle sensors. Intelligent vehicle sensing has seen increasing interest and application over the past decades with a wide range of applications in both driver assistance systems and autonomous guidance systems alike. This PhD project builds upon the ongoing theme of work within the Durham research team on intelligent vehicle sensing such autonomous route proving, road sign detection, headlight tracking, GPS navigation augmentation and automotive stereo vision. This project specifically looks to leverage recent advances in real-time stereo vision for use with sensors currently deployed for other driver assistance system tasks for advanced on-vehicle reasoning tasks. The project will take the form of an industrial CASE studentship with the student primarily based at Durham University whilst ideally working for short industrial placement periods with JLR throughout the PhD. This represents a very good opportunity for a candidate interested in an applied research career, comprising both academic and industrial placement elements within the 3.5 year study programme. Jaguar Land Rover designs, develops, manufactures and sells Jaguar premium sports saloons and sports cars and Land Rover premium all-terrain vehicles (and related parts and accessories) through a global sales and distribution network.(http://www.jaguarlandrover.com/). An overview of related research work within the Durham team is available from http://www.durham.ac.uk/toby.breckon/demos/ which illustrates both work within the automotive vision domain and other computer vision / image processing projects in the group. Within Durham, the School of Engineering and Computing Sciences provides a internationally recognised research environment across both engineering and computing with over 80% of research output recognised as Internationally Excellent or World Leading (3* and 4*, REF 2014). The twin foci of “theoretical” and “practical” Computer Science research allow a specialized collection of researchers to strategically develop, support and coordinate research in collaboration with a wide range of industrial and public sector partners. This has resulted in over £10 million of research income (20092014). Recent work includes 3D computer vision for object recognition and inspection, automated ground robot and aerial target detection (MOD Grand Challenge Winners 2008, Stellar Team), airport baggage security screening and on-going automotive computer vision using low-cost on-board sensors. In general we are concerned with the novel application of image processing and computer vision approaches for the effective extraction of visual information from images. Entry Requirements: Applicants should have good background in any of computer science, artificial intelligence, engineering, physics or a related discipline with a strong programming ability in a high level language (preferably C/C++, Java or Python) and a highly competent mathematical background (especially algebra, statistics and geometry). Candidates should hold at least a 2:1 honours degree or equivalent in Computer Science, Engineering, Physics or a related technical discipline (Masters degree a plus). Prior experience in computer vision, image processing and/or machine learning is a plus although not essential. Funding: This studentship is only available to UK/EU nationals who have been resident in the UK for the last 3 years (see: http://www.epsrc.ac.uk/skills/students/help/eligibility/). Studentship awards are available to cover both tuition fees and a stipend in the form of a tax-free subsistence bursary for both (in line with EPSRC recommendations, http://www.epsrc.ac.uk/skills/students/help/minimumpay/). Non-EU applicants, or EU-applicants not residing in the UK, are not eligible for this award unless they can demonstrate a relevant connection to the UK. Whilst the above funded position is only open to UK/EU students the department does additionally recruit international PhD students from the rest of the world on a self-funding basis for related projects in computer vision (and maybe able to identify funding sources to which you can apply – see https://www.dur.ac.uk/ecs/postgraduate/resdeg/). How to apply: Applicants can make initial informal enquiries with Dr. Toby Breckon, toby.breckon@durham.ac.uk If you meet the eligibility criteria please make an application via the university applications page at: https://www.dur.ac.uk/postgraduate/apply/ Please note this is the only way we can accept applications and applications are not accepted by email. (Please specify project title: Computer Vision – JLR Autonomous Road Vehicles, supervisor: Dr. Toby Breckon, Engineering and Computing Science)