Funded (UK/EU and international students)
DepartmentSchool of Sport, Health, and Exercise Science
30 June 2023
Applications are invited for a fully-funded three year PhD to commence in October 2023.
This PhD studentship, based primarily within the Faculty of Science and Heath at the University of Portsmouth, is an exciting opportunity to do research that is directly relevant to the NHS. Fully funded by the University of Portsmouth, the successful candidate will join a collaborative, multidisciplinary team from the School of Sport, Health and Exercise Science and the School of Computing, with external collaboration with the University Hospitals Sussex NHS Foundation Trust.
The successful candidate will join the Physical Activity, Health and Rehabilitation Thematic group at the University of Portsmouth, led by Dr Zoe Saynor, and will be based primarily at the School of Sport, Health and Exercise Science. Additional work may also take place at local hospital sites and involve working with clinical colleagues at University Hospitals Sussex NHS Foundation Trust. You will work as part of a team with your supervisors and will have the opportunity to undertake multiple research activities.
Successful applicants will receive a bursary to cover tuition fees for three years and a stipend in line with the UKRI rate (£17,688 for 2022/23). Bursary recipients will also receive a £1,500 p.a. for project costs/consumables.
The work on this project will be reactive to results but could involve:
- Evaluating mobility in older adults admitted to acute hospitals
- Working on predictive models using mobility assessments of older adults admitted to hospital
- Exploring the views of older people, their family members and health professionals around their experiences of hospital immobility
When admitted to hospital, older people spend most of their time immobile, despite their ability to walk. This can lead to multiple adverse health outcomes. The overall aim of this project is to explore the use of an objective measure of mobility as an early predictor of deterioration and discharge destination for older people admitted to hospital. This project will build on previous work from the supervisory team and the successful candidate will benefit from wide clinical and research networks established by the supervisory team. Direct links to the NHS mean a great opportunity of doing research with direct impact on patient care.
You'll need a good first degree from an internationally recognised university (minimum upper 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.
Experience or good understanding of both quantitative and qualitative research methods is important. Clinical experience, or experience of working or collaborating with older adults and their families will also be relevant, but not a requirement. This opportunity will suit you, if you are motivated to work on translational research that will directly improve clinical practice. Strong work-ethic, discipline, resilience and excellent communication skills are essential requirements. Applications will be considered from people with a wide range of backgrounds, such as computer science, sport and exercise science, psychology, physiotherapy, nursing, occupational therapy or medicine, or a combination of these.
How to apply
We’d encourage you to contact Dr Carolina Gonçalves (email@example.com) to discuss your interest before you apply, quoting the project code.
When you are ready to apply, you can use our online application form. 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.
If you want to be considered for this funded PhD opportunity you must quote project code SHES8220723 when applying.