Research Fellow in AI and Machine Learning for Innovative Quality Engineering - FAC0136-1

Brunel University London - College of Engineering Design and Physical Sciences

Salary (R1-PhD. 30-36): £32,004 to £38,183 pa plus London Weighting (£2,166)

Full-Time, Fixed Term (48 months)

Applications are invited for a full-time Research Fellow to conduct collaborative research in quality engineering and smart technology, as part of Phase I projects in the interdisciplinary research Institute of Innovative Quality Engineering and Smart Technology (I2QUEST).

The I2QUEST is an international Industry - University - Research innovation platform, recently launched with Sichuan Mingxin Investment Group (SMIG), Brunel University London (BUL) and the National Physics Laboratory (NPL) as its core collaborating partners, supported by Chengdu High-tech Zone, with its vision to be a world leading Centre of Excellence in innovative quality engineering and smart technology. The I2QUEST has received an investment of about £2.4m for Phase I projects and a total investment of £20m for further research with participations of more academic and industrial partners. Its mission is to help industries and businesses to innovate and improve the quality of their products, processes and services through promoting the best quality engineering practices and providing smart system solutions.

This post is fixed term for four years from the date of appointment and is planned to begin in October 2017. The fellow will be based in the College of Engineering, Design and Physical Sciences at BUL.

This post will focus particularly on AI and machine learning for innovative quality engineering. The fellow will develop knowledge based systems, machine learning and AI solutions (including VR/AR) for quality engineering applications. S/he will also develop natural human-computer interaction system (e.g. voice interface).

The fellow is expected to travel to China occasionally and will play an important role in establishing and developing collaborative relationships between BUL/NPL and SMIG. S/he will also participate in related activities, including industrial consultancy, grant applications, conferences, as well as other occasional duties such as administration or teaching.

The fellow is required to have received the degree of PhD (or shortly to be awarded) in an appropriate discipline such as computer science, software engineering, information engineering, AI, robotics and cognitive science. Applicants are expected to demonstrate good knowledge in quality engineering management tools, machine learning and AI. The successful candidate should have good programming skills in Python, Matlab, VBA, JavaScript and C. Experience in cloud computing and/or IOT will be desirable. Also essential are excellent research skills and a proven track record in conducting high quality research (as evidenced by publications in peer reviewed journals).

For an informal general discussion regarding the above post, please contact Dr QingPing Yang (

For further details and to apply please visit

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