Cyber-Security and Deep Learning for Autonomous Vehicles investigating the intersection of AI and cyber security

The project will investigate the intersection of AI and cyber-security, specifically targeting visual navigation systems based on deep learning for autonomous vehicles.  The PhD will develop new tools to evaluation the attack surface and defend against malicious stimuli to AI visual navigation systems, ultimately contributing to the long term safety of autonomous vehicles in society. The PhD is co-supervised between the Centre for Vision Speech and Signal Processing (CVSSP) and Surrey's GCHQ accredited Centre for Cyber Security (SCCS)

CVSSP is a leading UK research centre in audio-visual signal processing, computer vision and machine learning. Our Centre is one of the largest in Europe with over 120 researchers and a grant portfolio in excess of £18.5million, bringing together a unique combination of cutting-edge sound and vision expertise. Our aim is to advance the state of the art in multimedia signal processing and computer vision, with a focus on image, video and audio applications. Our Centre has a robust track-record of innovative research leading to technology transfer and exploitation in biometrics, creative industries (film, TV, games, VR), mobile communication, healthcare, robotics and consumer electronics.

CVSSP is part of the Department of Electrical and Electronic Engineering and has -been ranked third in the UK in the Guardian newspaper league table 2017. The Department of Electrical and Electronic Engineering achieved a 92.9% overall satisfaction for NSS 2017 and is rated seventh in the UK for Electronic Engineering in the The Complete University Guide 2018.

Applicants should have:

• A first class or 2:1 honours degree (or equivalent overseas qualification) in an appropriate discipline (e.g. engineering, computer science, signal processing, applied mathematics, and physics)
• You should be able to demonstrate excellent mathematical, analytic, programming skills
• Previous experience in computer vision, machine/deep learning, or augmented reality would be advantageous.
• Non-native speakers of English will normally be required to have IELTS 6.5 or above (or equivalent) with no sub-test of less than 6