Towards a machine learning model of sleep to accelerate health research
We are recruiting new Doctoral Researchers to our EPSRC funded Doctoral Training Partnership (DTP) PhD studentships starting 1 October 2024. Applications are invited for the project title ‘Towards a machine learning model of sleep to accelerate health research’.
Successful applicants will receive an annual stipend (bursary) of £21,237, including inner London weighting, plus payment of their full-time home tuition fees for a period of 42 months (3.5 years).
You should be eligible for home (UK) tuition fees - there are a very limited number (no more than three) of studentships available to overseas applicants, including EU nationals, who meet the academic entry criteria including English Language proficiency.
You will join the internationally recognised researchers in the Department of Brunel Design School research and PhD programmes | Brunel University London
The Project
Sleep monitoring holds potential for predicting a range of health conditions. However, machine learning (ML) models capable of fully analysing the complexity of patient data from specialised sleep clinics are missing. This project will develop early-stage ML models of sleep combined with prototypes of intuitive digital interfaces for clinicians and health researchers, developed using user-centred design processes with significant involvement of target users and stakeholders. Reducing prediction bias, lowering barriers to technology adoption, and designing for equitability in health research and clinical workflows will be key priorities. The team will rely on public sleep data from 40,000+ patients with varying degree of detail about medical history and demographics, among other datasets. Clinical insights will be available via an ongoing collaboration between Brunel and Royal Brompton and Harefield Hospitals. The successful applicant will have access to multidisciplinary academic expertise via the Brunel Centre for AI and will work within a research consortium including University College London, King’s College London, and industry partners.
Please contact Dr Federico Colecchia at Federico.Colecchia@brunel.ac.uk for an informal discussion about the studentships.
Eligibility
Applicants will have or be expected to receive a first or upper-second class honours degree in an Engineering, Computer Science, Design, Mathematics, Physics or a similar discipline. A Postgraduate Masters degree is not required but may be an advantage.
Skills and Experience
Applicants will be required to demonstrate the following skills:
- A self-directed proactive attitude combined with excellent time and project management skills.
- Excellent communication and teamwork skills.
- Proficiency with modern data science and machine learning techniques and knowledge of and experience using user-centred design processes or similar methods of aligning technology development with user requirements, needs, and expectations.
- Ability and motivation to work on an interdisciplinary research project at the intersection of machine learning with user-centred design.
- Applicants must be available to commit full time to the research for the duration of the project. The research will take place on the Brunel campus.
How to apply
There are two stages of the application:
1.Applicants must submit the pre-application form via the following link
https://brunel.onlinesurveys.ac.uk/epsrc-dtp-24-25-pre-application-form-brunel-university-lon
by 16.00 on Friday 5th April 2024.
2.If you are shortlisted for the interview, you will be asked to email the following documentation in a single PDF file to cedps-studentships@brunel.ac.uk within 72hrs.
- Your up-to-date CV;
- Your Undergraduate degree certificate(s) and transcript(s) essential;
- Your Postgraduate Masters degree certificate(s) and transcript(s) if applicable;
- Your valid English Language qualification of IELTS 6.5 overall (minimum 6.0 in each section) or equivalent, if applicable;
- Contact details for TWO referees, one of which can be an academic member of staff in the College.
Applicants should therefore ensure that they have all of this information in case they are shortlisted.
Interviews will take place in April/May 2024.