Funding

Self-funded

Project code

COMP6301025

Department

School of Computing

Start dates

October, February and April

Application deadline

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 will:

  •    Applying the latest Artificial Intelligence techniques
  •    Developing technologies that can help improve people’s health and wellbeing
  •    Experimenting with realistic application scenarios and interacting with potential users of your research

Context

Applications of AI in health and wellbeing technologies offer unprecedented opportunities for enhancing our health and wellbeing, for preventive and personalised care, and for promoting independence. Wearable devices, smart environmental sensors, and user feedback can generate valuable data that can be processed by AI algorithms to contribute to early disease detection, management of long term conditions, and assisting with everyday activities.  

This PhD is about investigating how a range of AI techniques, including machine learning, computer vision, and natural language processing, can be used to develop next generation health technologies focusing on wellbeing outside clinical settings. The aims are to help people stay healthy at home and in a workplace, to facilitate early hospital discharge, and to promote healthy ageing. Examples include ambient assisted living, health apps, and employee wellbeing platforms.

We are looking for motivated numerate candidates, wishing to combine their interest in AI with a passion for innovation to research novel practical applications of AI in health and wellbeing technologies. The successful candidate will work within a team of academics and researchers with an established track record in applied AI for health and wellbeing, and strong links with care organisations, technology providers, and end user groups. We have a friendly and supportive research environment and excellent research facilities, including  a fully instrumented residential house providing a real-world environment for experimentation with various technologies,  an IBM PowerAI Vision platform, and the Sciama supercomputer for demanding machine learning tasks

Funding

Visit the research subject area page for fees and funding information for this project.

Funding availability: Self-funded PhD students only. 

PhD full-time and part-time courses are eligible for the UK Government Doctoral Loan (conditions apply).

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

The entry requirements for a PhD or MPhil include an upper second class honours degree or equivalent in a relevant subject or a master's degree in an appropriate subject. Exceptionally, equivalent professional experience and/or qualifications will be considered. All applicants are subject to interview.

If English is not your first language, you'll need English language proficiency at a minimum of IELTS band 6.5 with no component score below 6.0.

If you don't meet the English language requirements yet, you can achieve the level you need by successfully completing a pre-sessional English programme before you start your course.

Good numeracy and programming skills. Knowledge of machine learning, computer vision, or natural language processing, as well as experience with sensors are helpful.

 

How to apply

We’d encourage you to contact Dr Rinat Khusainov  (rinat.khusainov@port.ac.uk) to discuss your interest before you apply, quoting the project code.

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: COMP6301025