An investigation of how growth and maturation affects injury risk in adolescent athletes and how AI might be used to predict sports injury risk during adolescence

Summary

This is an exciting project involving collaboration between the School of Health Sciences and the School of Computing, Engineering and Intelligent Systems at UU.

You will investigate the following:

- Examine at what stage of maturation highest injury risk presents- Explore potential sex-specific associations between biological maturation and injury risk in adolescent athletes

- Investigate if these are comparable- Explore correlations between types and severities of injuries and stage of maturation

- Investigate how Artificial Intelligence may be used to identify periods of elevated injury risk in adolescent populations.

Aims:

1. To investigate the relationships between biological maturation, growth velocity and injury risk in male and female adolescent sports participants.

2. To investigate the feasibility of developing interpretable AI models to support sex-specific and maturity-informed injury prevention strategies.

Objectives:

1. Systematically review the current evidence examining relationships between growth and maturation and injury risk in male and female adolescent athletes, identifying sex-specific differences.

2. Quantify the relationship between components / identifiers of physical maturation and growth velocity (PHV) and injury incidence in male and female adolescent athletes.

3. Establish interactions between maturation, training load and physical wellness and injury risk.

4. Explore the feasibility of developing and evaluating interpretable AI models that use maturation, training load and physical wellness data to identify periods of elevated injury risk in adolescent athletes.

Methods:

1. Conduct quantitative and qualitative activities that may include the following; anthropomorphic measurements, injury surveillance, collecting training load, GPS and wellness data (sleep quality / duration, fatigue, muscle soreness, stress etc.), co-design, focus groups, workshops / seminar activities.

2. Develop IPP guidelines for adolescent athletes through engagement with key stakeholder groups.

3. Working with colleagues in the School of Computing and Intelligent Systems, develop and evaluate interpretable AI-based injury risk stratification models using maturation, training load and wellness data.

AccessNI clearance required

Please note, the successful candidate will be required to obtain AccessNI clearance prior to registration due to the nature of the project.

Essential criteria

Applicants should hold, or expect to obtain, a First or Upper Second Class Honours Degree in a subject relevant to the proposed area of study.

We may also consider applications from those who hold equivalent qualifications, for example, a Lower Second Class Honours Degree plus a Master’s Degree with Distinction.

In exceptional circumstances, the University may consider a portfolio of evidence from applicants who have appropriate professional experience which is equivalent to the learning outcomes of an Honours degree in lieu of academic qualifications.

Desirable Criteria

If the University receives a large number of applicants for the project, the following desirable criteria may be applied to shortlist applicants for interview.

• Practice-based research experience and/or dissemination
• Experience or knowledge of research methods or other approaches relevant to the subject domain
• Work experience relevant to the proposed project
• Track record of peer reviewed publications
• Experience of presentation of research findings
• Relevant professional qualification

Equal Opportunities

The University is an equal opportunities employer and welcomes applicants from all sections of the community, particularly from those with disabilities.

Appointment will be made on merit.

Funding and eligibility

This project is funded by:

• Department for the Economy (DfE)
• Vice Chancellor's Research Scholarship (VCRS)

PhD Scholarships are available for this project and will cover:

• Tuition fees.
• A maintenance allowance of approximately £22,000 (exact rate is to be confirmed) per annum for three years, subject to satisfactory academic performance.
• A Research Training Support Grant (RTSG) of approximately £900 per annum.

To be eligible for these scholarships applicants must: be a UK or Irish national; or have pre-settled or settled status; or have indefinite leave to remain or enter.

Applicants should also meet the residency criteria which requires that they have lived in the EEA, Switzerland, the UK or Gibraltar for at least the three years preceding the start date of the research degree programme i.e. September 2027.

Applicants who already hold a doctoral degree or who have been registered on a programme of research leading to the award of a doctoral degree on a full-time basis for more than one year, or part-time equivalent, funded from any source, including self-financing students, are NOT eligible to apply for an award.

Students in full-time employment are not eligible for an award.

Due consideration should be given to financing your studies.

Part-time PhD scholarships may be available at a 0.5 pro rata rate of the full-time scholarship, which would require a six-year registration period.

The University will award a successful candidate one of the following scholarships for the project, depending on the funding available at the time an admissions offer is made:

1. Department for the Economy (DfE) PhD Scholarships
2. Vice Chancellor’s Research Scholarships (VCRS)

Please note that the Terms and Conditions for scholarships are subject to change for 2027/28.