Job Description

Department of Computer Science

TrainFX

Computer Vision and Machine Learning Specialist (KTP Associate)

Period:

13.5 months (Full time)

Salary:

34,000 to 38,000 per annum (Starting salary to be confirmed on offer of appointment), plus 4,500 training budget

Project Title:

AI-empowered Vision System for Passenger Counting and Smart Passenger Information System (PIS)





This project is a Knowledge Transfer Partnership (KTP) project between Loughborough University and TrainFX, funded by UKRI Innovate UK, with 13.5 months remaining.





This is an exciting opportunity for a forward-thinking and ambitious specialist in computer vision and machine learning to join a company that specialises in providing SAAS services to the Rail Industry. Working with some of the biggest Train Operators in the UK, you will be joining a company that finds ways to help make services to Rail passengers better, faster and more accessible for everyone.





The project aims to develop computer vision technology for automated counting of passenger numbers and monitoring occupancy in train carriages and integrate the real-time passenger loading information into TrainFX Smart-PIS (Passenger Information System).





The AI-empowered Smart-PIS will provide dynamic data acquisition and real-time, personalised information supporting travellers, railway operators and service providers. The system will improve current service efficiency, promote passenger satisfaction, and provide the potential for new services through affordable technologies. It is the first of this kind of innovative system in railway which enables bespoke customisation towards rail industry objectives.





The whole KTP project will be delivered through dual Associate workplans by two KTP Associates.KTPs aim to help businesses improve their competitiveness and productivity through the better use of knowledge, technology and skills that reside within the UK Knowledge Base.





The candidate will be hold PhD (or near completion) or MSc in Computer Science or closely allied disciplines and will have solid skills to support software QA and optimise I/O performance.





The KTP Associate will be based primarily at the company TrainFX premises in Derbyshire and will also spend some time at Loughborough University with the academic team. The Associate will be supervised by an academic team led by Prof. Baihua Li and Prof. Qinggang Meng who are experts in AI and computer vision at Department of Computer Science, Loughborough. The Associate will form an integral part of the TrainFX research and development team, working closely with the TrainFX supervisory team and company partners.





For more information refer to the and Person Specification.

Informal enquiries

Informal enquiries should be made to the Lead Academic, Professor Baihua Li (b.li@lboro.ac.uk).

The closing date for receipt of applications is 25 June 2025.

The interviews will take place on or around 3 and 4 July 2025.