Ambient Assisted Living Technologies
PhDs and postgraduate research
Self-funded PhD students only
School of Computing
October and February
Applications accepted all year round
Applications are invited for a self-funded, 3 year full-time or 6 year part-time PhD project.
The PhD will be based in the School of Computing and will be supervised by Dr Rinat Khusainov and Dr Richard Curry.
The work on this project could involve:
- Addressing the need to provide safe living environments for people with care needs and help families look after their loved ones
- Applying the latest Artificial Intelligence and Computer Vision techniques to real life data
- Experimenting with various assistive technologies in realistic deployment environments
Ambient Assisted Living (AAL) is concerned with using various technological solutions to allow people with additional care needs live independently in their preferred environment. AAL is of great importance for future healthcare services due to increases in the costs of traditional care models, caused by the growing elderly population and the number of people with long-term health conditions. There has been a considerable interest in AAL technologies recently from the government and industry alike. However, these systems have so far seen rather limited use with relatively basic AAL examples primarily targeting various domestic emergencies, like wearable fall detection devices or home water leak sensors.
The aim of this project is to investigate the barriers for adoption of more sophisticated systems, which could carry out more complex monitoring of activities of daily living to ensure wellbeing and safety of people living on their own. There are a number of aspects that can be covered in this work, including the performance of current data processing techniques, the choice of sensor technologies and trade-offs between wearable and environmental sensors, the usability requirements, and security and privacy concerns.
The successful candidate will work within a team of academics and researchers with a track record in AAL, including links with care and housing providers. The project will utilise a bespoke research facility consisting of a fully instrumented residential house providing a real-world environment for experimentation with various technologies and collection of research data. The School also boasts excellent computing facilities including an IBM PowerAI Vision platform for image and video analysis, and a vibrant and supportive research environment.
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).
2021/2022 fees (applicable for October 2021 and February 2022 start)
PhD and MPhil
Home/EU/CI full-time students: £4,500 p/a**
Home/EU/CI part-time students: £2,250 p/a**
International full-time students: £17,600 p/a*
International part-time students: £8,800 p/a*
PhD by Publication
External candidates: £4,407*
Members of staff: £1,720
All fees are subject to annual increase. 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.
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.
You'll need a good first degree from an internationally recognised university 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.
Good numeracy and programming skills are an advantage. Knowledge of AI, computer vision, or sensors is helpful.
How to apply
When you are ready to apply, please follow the 'Apply now' link on the Computing PhD subject area page and select the link for the relevant intake. 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.
When applying please quote project code: COMP5441021