Self-funded PhD students only

Project code



School of Sport, Health and Exercise Science

Start dates

Closing date

Applications accepted all year round

This 3-year self-funded PhD will be based in the Department of Sport and Exercise Science and will be supervised by Dr Martina Navarro and Dr Matt Dicks.

The work on this project will:

  • reveal the underlying mechanisms of the visual control of braking during cycling
  • identify key aspects in cycling traffic accidents reduction
  • Better inform city planners on how to design efficient cycle paths when planning sustainable cities

The purpose of this PhD project is to develop understanding of braking in cycling and critically examine how a performer’s skill and environmental constraints interact during this task.

As an increasingly wide-spread form of transportation, cycling is a goal-directed locomotion task mainly guided by visual information. According with the gaze constraints model, riders can obtain visual information from two regions: the “near” region for stability and vehicle control, and the “far” region for guidance and hazard perception.

The allocation of gaze in the first region would increase with task complexity and decrease according with performers’ riding skills, while gaze in the second region would increase with cycling speed and environment unpredictability.

An increase in both direct control and anticipation increase attentional demand and mental workload. Higher levels of attentional demand and mental workload can increase the probability of an accident as soon the task-demands increase. Therefore, a better comprehension of the relationship between performer perception-action and environmental constraints during braking in cycling can offer valuable information to city planners.

To test the gaze constraint model, this project will critically examine the effects of cycling speed, path width and curvature, cycling experience and environmental cues on gaze behaviour and performance of cyclists during braking. This project will also offer an exciting opportunity to test “the best” cycle path planning suggested by the results from the gaze constraint model experiments.

In Phase 1 of the project, eye-tracking technology will be utilized to measure inexperienced and experienced cyclists gaze patterns when cycling and braking in a natural controlled environment (e.g. sports hall).

During this phase, different cycling conditions will be created by manipulating cycling speed, path curvature and width and environmental cues to test their performance when they have to stop predictably and unpredictably. Results from Phase 1 will inform the design of virtual cities in a virtual environment in order to safely test the “best” paths for sustainable cities (Phase 2).

In Phase 2, eye movements and riding performance will also be measured, and these results will be compared with the natural condition. It’s expected that the project will deliver the three following outcomes:

  • Reveal the underlying mechanisms of the visual control of braking during cycling
  • Identify key aspects in cycling traffic accidents reduction
  • Better inform city planners on how to design efficient cycle paths when planning sustainable cities

Fees and funding

Funding Availability: Self-funded PhD students only

PhD full-time and part-time courses are eligible for the UK Government Doctoral Loan (UK and EU students only).

2019/2020 entry

Home/EU/CI full-time students: £4,327 p/a*

Home/EU/CI part-time students: £2,164 p/a*

International full-time students: £15,900 p/a*

International part-time students: £7,950 p/a*

By Publication Fees 2019/2020

Members of staff: £1,610 p/a*

External candidates: £4,327 p/a*

*All fees are subject to annual increase

2020/2021 entry (for October 2020 and February 2021 entries)

Home/EU/CI full-time students: £4,407 p/a

Home/EU/CI part-time students: £2,204 p/a

International full-time students: £16,400 p/a

International part-time students: £8,200 p/a

PhD by Publication

External candidates £4,407 p/a

Members of staff £1,680 p/a*

2021/2022 entry (for October 2021 and February 2022 entries)

PhD and MPhil

Home/EU/CI full-time students: £4,407 p/a*

Home/EU/CI part-time students: £2,204 p/a* 

International full-time students: £17,600 p/a

International part-time students: £8,800 p/a

All fees are subject to annual increase.

PhD by Publication

External Candidates £4,407 p/a*

Members of Staff £1,720 p/a*

If you are an EU student starting a programme in 2021/22 please visit this page.

*This is the 2020/21 UK Research and Innovation (UKRI) maximum studentship fee; this fee will increase to the 2021/22 UKRI maximum studentship fee when UKRI announces this rate in Spring 2021. 

Bench fees

Some PhD projects may include additional fees – known as bench fees – for equipment and other consumables, and these will be added to your standard tuition fee. Speak to the supervisory team during your interview about any additional fees you may have to pay. Please note, bench fees are not eligible for discounts and are non-refundable.

Entry requirements

Entry requirements

  • You'll need a good first degree from an internationally recognised university (minimum second class or equivalent, depending on your chosen course) or a Master’s degree in an appropriate subject
  • In exceptional cases, we may consider equivalent professional experience and/or Qualifications
  • English language proficiency at a minimum of IELTS band 6.5 with no component score below 6.0

  • We’d welcome applications from candidates with a background in human factors, motor control, experimental psychology, or a related subject area
  • The successful applicant will receive training and support to develop the skills that will enable the novel integration of eye movement (eye-tracking) measures in a virtual reality technology
  • Experience in both eye tracking and virtual reality isn’t mandatory but valuable
  • We are seeking to appoint an enthusiastic and committed candidate with excellent interpersonal and organisational skills as well as an understanding of quantitative research methods.

How to apply

Please contact Dr Martina Navarro ( to discuss your interest before you apply, quoting the project code.

When you're ready to apply, you can use our online application form and select ‘Sport Science’ as the subject area. Make sure you submit a personal statement, proof of your degrees and grades, details of two referees, proof of your English language proficiency and an up-to-date CV.

Our ‘How to Apply’ page offers further guidance on the PhD application process.

Please note, to be considered for this self-funded PhD opportunity you must quote project code SPES4880219 when applying.