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Applying Deep Learning to Understand Player Movement Patterns and Sports Specific Movement Classifications

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  • Full or part time
    Dr B Jones
  • Application Deadline
    No more applications being accepted
  • Competition Funded PhD Project (Students Worldwide)
    Competition Funded PhD Project (Students Worldwide)

Project Description

The Carnegie Adolescent Rugby Research (CARR) is pleased to offer the following PhD Studentship project to progress the field of athlete workload and performance monitoring, the recruited PhD students will analyse frequently collect micro technology data, to provide new insights. Within sport, data are frequently measured and evaluated from velocity-derived metrics from GPS technology. In addition to GPS, accelerometers, gyroscopes and magnetometers are also embedded within micro technology devices. These allow specific movements, sequence of movements and player movement patterns to be classified, which are rarely explored. By working closely with international coaches within the EPU, the impact of manipulating game constraints will be evaluated which will support talent identification, talent development, athlete physical preparation and injury prevention practices across a range of sports. The candidate will have experience working with sports technology, advanced data science and statistical analyses techniques.

Please visit the application link to view how to apply, complete the application form and return to [Email Address Removed] including your research proposal, scanned copies of your degree certificates (e.g. undergraduate or masters degree certificates) and transcripts, scanned copies of your English language requirements, scanned copies of your passport and previous UK visas if applicable.

Interviews will be held at our Headingley Campus on 1st, 2nd and 4th July 2019

Funding Notes

A stipend of £15,009 per annum (pro-rata into 12 monthly payments) is provided with UK/EU Fees paid for a period of three years.
A laptop, office space and £1000 to support the research project are also provided

How good is research at Leeds Beckett University in Sport and Exercise Sciences, Leisure and Tourism?

FTE Category A staff submitted: 48.60

Research output data provided by the Research Excellence Framework (REF)

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