PhD Studentship: AI/machine Learning based Algorithm and Software Development for Action Event Detection and Football Player Analytics: Funded PhD Studentship with StatMetrix

Loughborough University

Application details:
Reference number: CDTEI_Li
Start date of studentship: July or October 2018
Closing date of advert: 31st January 2018
Interview date: TBC

Supervisors:
Primary supervisor: Dr Baiihua Li
Secondary supervisor: TBC

We are seeking excellent candidates with interests in Artificial Intelligence (AI), machine learning and deep learning who want to study at a top 10 UK research-led University whilst working with industrial partners. 

This project is part of the EPSRC Centre for Doctoral Training in Embedded Intelligence. In choosing this project you’ll work alongside academics that are leaders in their field and benefit from a four-year studentship award that includes an enhanced EPSRC tax-free annual stipend of at least £17,553 per annum and UK/EU tuition fees. Furthermore, you will have access to a personal training budget of £10,000, which is in addition to a research budget and support from academic members of staff and industrial partners.

Loughborough University aims to ensure equality for men and women. We follow the principles of the Athena SWAN Charter by wishing to attract, support, and reward women in STEMM at all career stages.

Full Project Detail:
The studentship is co-sponsored by sports technology company, StatMetrix and you will join a growing research group within the Department of Computer Science. This project is an exciting opportunity to develop machine learning and pattern recognition based algorithms and software to address several challenges in football player analytics using video and wearable sensor data. We aim to detect performance relevant events and motion data, such as ball passing, running, shot, speed, position, direction and trajectories.  The developed intelligent software will provide performance data insights for football coaches and scouts to better understand player performance trends and identify talented players.

Find out more: www.cdt-ei.com http://statmetrix.co/

Entry requirements:
Applicants should have, or expect to achieve, at least a 2:1 Honours degree (or equivalent) in related Computer Science, Engineering or Mathematics degree with strong programming skills (e.g. Matlab, C++, Python) and knowledge of artificial intelligence and computer vision. A relevant Master’s degree and/or experience in machine learning and deep learning is desirable, as is a passion in intelligent systems, sports technology and football performance analytics.

Applicants must meet the minimum English Language requirements, details available on the website.

Funding information:
The studentship is for four years and provides a tax free stipend of £17,553 per annum for the duration, plus tuition fees at the UK/EU rate. In order to qualify for a full award, all applicants must meet the EPSRC eligibility criteria including the minimum UK residency requirement https://www.epsrc.ac.uk/skills/students/help/eligibility/.  

Contact details:
Name: Dr Baihua Li
Email address: B.Li@lboro.ac.uk 
Telephone number: 01509 222 672
Enquiries about the application process and CDT programme can be made to cdt-ei@lboro.ac.uk. For answers to frequently asked questions about the CDT, visit the website.

How to apply:
All applications should be made online at http://www.lboro.ac.uk/study/apply/research/. Under programme name, select “CDT Embedded Intelligence Wolfson School”

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Advert information

Type / Role:

PhD

Location(s):

Midlands of England