Cyber-Security and Deep Learning for Autonomous Vehicles investigating the intersection of AI and cyber security
The Centre for Vision Speech and Signal Processing (CVSSP) seeks applications from high quality students for and funded studentship in Cyber-Security and Deep Learning for Autonomous Vehicles.
EPSRC Industrial Case studentship co-funded by Thales R&D. Funding will provide an annual tax-free stipend of approximately £14,553 and coverage of the home/EU tuition fees for 3.5 years.
Funding sourceDirectly Funded home and EU students
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
How to apply
Shortlisted applicants will be contacted directly to arrange a suitable time for an interview.
For enquiries contact Dr John Collomosse (J.Collomosse@surrey.ac.uk) indicating your areas of interest and including your CV with qualification details (copies of transcripts and certificates.
We acknowledge, understand and embrace diversity.
The deadline for applications is 15 July 2018. Applications will be considered as they arrive and may close earlier if the right candidate is identified.