​​Real-Time prediction of Epileptic Seizures using Machine Learning​

Summary

Interested in changing the lives of people living with Epilepsy?

Epilepsy is a prevalent, serious neurological condition which affects 50 million people worldwide and ~600,000 in the UK. The greatest obstacle for PWE (People living With Epilepsy) is the unpredictability of their seizures. Some PWE can experience up to 200 seizures in a single day. Imagine how debilitating that is! Additionally, many seizures begin without any warning, so PWE could be carrying out a normal everyday task, such as crossing the road, when their body involuntarily falls to the ground. Some tasks that we take for granted are dangerous for PWE.

This project complements a wider research project called Atmosphere: Artificial intelligence To Maximise and Optimise Seizure Prediction to EmpoweR people with Epilepsy. It exploits ML algorithms, coupled with an intuitive smartphone app, to forecast an individual’s risk of experiencing a seizure using data obtained from wearable devices. All development within the project is carried out with clinicians and PWE.

ML techniques depend heavily on substantial quantities of input data to produce accurate predictions. This PhD will focus on ML and aims to enhance prediction of epileptic seizures by adopting state-of-the-art innovations and developments in ML, including causal models.

It addresses the following research questions:
* Can ML accurately predict seizure occurrence in a real-time, personalised manner?
* Can additional data metrics be measured/obtained via wearable devices to augment/validate ML models used in the prediction of seizures?
* Can causal modelling ML approaches be used to facilitate explainability and identify potential interventions to prevent seizures?

All your supervisors have long, track records of successful PhD supervision, covering all the topics of your research. So you know you will be very well supported. Come and join our team!

Let’s chat and see if this project is a good fit for you! Contact Liz on l.stuart1@ulster.ac.uk.

The School of Computing at Ulster University holds Athena Swan Bronze Award since 2016 and is committed to promote and advance gender equality in Higher Education. We particularly welcome female applicants, as they are under-represented within the School.

Essential criteria

Applicants should hold, or expect to obtain, a First or Upper Second Class Honours Degree in a subject relevant to the proposed area of study.

We may also consider applications from those who hold equivalent qualifications, for example, a Lower Second Class Honours Degree plus a Master’s Degree with Distinction.

In exceptional circumstances, the University may consider a portfolio of evidence from applicants who have appropriate professional experience which is equivalent to the learning outcomes of an Honours degree in lieu of academic qualifications.

• Sound understanding of subject area as evidenced by a comprehensive research proposal
• A demonstrable interest in the research area associated with the studentship

Desirable Criteria

If the University receives a large number of applicants for the project, the following desirable criteria may be applied to shortlist applicants for interview.

• First Class Honours (1st) Degree
• Masters at 70%
• For VCRS Awards, Masters at 75%
• Experience using research methods or other approaches relevant to the subject domain
• Work experience relevant to the proposed project
• Publications - peer-reviewed
• Experience of presentation of research findings

Equal Opportunities

The University is an equal opportunities employer and welcomes applicants from all sections of the community, particularly from those with disabilities.

Appointment will be made on merit.

Funding and eligibility

This project is funded by:

• Department for the Economy (DfE)
• Vice Chancellor's Research Scholarship (VCRS)

Our fully funded PhD scholarships will cover tuition fees and provide a maintenance allowance of £19,237 (tbc) per annum for three years (subject to satisfactory academic performance).  A Research Training Support Grant (RTSG) of £900 per annum is also available.

These scholarships, funded via the Department for the Economy (DfE) and the Vice Chancellor’s Research Scholarships (VCRS), are open to applicants worldwide, regardless of residency or domicile.

Applicants who already hold a doctoral degree or who have been registered on a programme of research leading to the award of a doctoral degree on a full-time basis for more than one year (or part-time equivalent) are NOT eligible to apply for an award.

Due consideration should be given to financing your studies.