College of Engineering, Design & Physical Sciences

Electronic and Computer Engineering

Research Fellow

Ref No 13605

Salary (R1): £35,963 - £42,488 per annum including London Allowance

Full Time, fixed term for up to 3 years

This industry funded project is seeking to appoint a Research Fellow for an exciting opportunity to carry out research on artificial intelligence (AI) powered techniques, which will then be employed to analyse massive video data streamed from high-definition surveillance cameras for operation safety monitoring and enhancement in the manufacturing sector. Currently the manufacturing industry is undergoing digitalisation empowering themselves with the latest IT technologies such as AI, Industrial Internet of Things, Big Data and Industry 4.0.

The successful candidate will work on the development of AI techniques for extracting features from both normal/abnormal human operational behaviours and building operation safety knowledge graph. The focus will be on the development of deep learning techniques for learning and training of operational behaviours based on data mining and reasoning of the constructed knowledge graph. Considering the potentially ever growing volumes of video data, the successful candidate will also work on the development of high performance computing techniques using GPU and multiple CPU core computing platforms to speed up the computation of the AI techniques to achieve real-time operational safety monitoring and alarm raising by analysing the events detected from the video camera data channels.

The successful candidate should have a PhD degree in Computer Science, or a related field of science or engineering. Research experience and programming skills in AI related areas such as Computer Vision, Deep Gaussian Processes (DGPs), Transfer Learning are essential. The successful candidate should also have good communication and presentation skills and be a proactive team player.

Informal enquiries should be directed to Prof. Maozhen Li (Maozhen.li@brunel.ac.uk)

Closing date for applications: 27 September 2020