Job title
AI/ML Scientist for Sports Performance Analytics (KTP Associate)
Job reference
REQ241094
Date posted
05/12/2024
Application closing date
12/01/2025
Location
London
Package
£38,000 - £44,000 per annum inclusive of London Weighting (Starting salary to be confirmed on offer of appointment), plus £2000 per annum training budget.
Job description
School of Science and ai.io
AI/ML Scientist for Sports Performance Analytics (KTP Associate)
Full time, fixed term for 30 months
Please note that the successful applicant must be in post no later than 22 June 2025 due to funding.
Location: primarily based in London
Salary: £38,000 - £44,000 per annum inclusive of London Weighting (Starting salary to be confirmed on offer of appointment), plus £2000 per annum training budget
Key words : deep learning, computer vision, machine learning, AI, artificial intelligence, computer science, football video analysis, action quality assessment, machine vision, AI for sports.
Project Title: AI-powered Talent Scouting: Revolutionising Automated Football Player Performance Assessment
About the role
Our vision is to democratise access to talent development by allowing players to showcase their abilities via mobile technology, enabling scouts to assess them with a fair, data-driven approach.
Join ai.io to shape the future of football scouting with AI, making talent discovery accessible and objective.
This is a 30-month Knowledge Transfer Partnership (KTP) project between Loughborough University and AI.IO, funded by UKRI Innovate UK.
A Knowledge Transfer Partnership (KTP) is a unique collaborative partnership between businesses and universities to create a positive impact and drive innovation.
The KTP Associate works with the business to implement innovative solutions to identified business challenges, using the knowledge and expertise gained through their academic training. The academic partner (Loughborough University) supports and guides the KTP Associate throughout the project.
The associate will be required to develop and integrate state-of-the-art deep learning and computer vision technology to analyse mobile video data captured by customers, providing actionable insights and automating the talent discovery, analysis, and development process. It will improve drill metric scoring and feedback by accurately identifying the playing surface, players, and equipment.
The primary focus will be on vision-based object detection, tracking, and movement interpretation. Knowledge of large language models will also enhance credibility.
The KTP Associate will be based primarily at ai.io, Shaftesbury House, 151 Shaftesbury Ave, London, WC2H 8AL and will also spend some time at Loughborough University with the academic team, led by Prof. Meng, Prof. Li and Dr Saada, who are experts in AI and vision-based human motion analysis in the Department of Computer Science, Loughborough.
For more information refer to the Job Description and Person Specification.
Informal Enquiries Informal enquiries should be made to the Lead Academic, Professor Qinggang Meng [email protected] , Professor Baihua Li, [email protected]
The closing date for receipt of applications: Sunday 12 January 2025
The interviews will take place: During the week commencing 20 January 2025