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Enabling artificial intelligence for clinical neurophysiology


   Post Graduate Research School

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  Dr David Western  No more applications being accepted  Funded PhD Project (European/UK Students Only)

About the Project

An opportunity to apply for a funded full-time PhD in the Faculty of Environment and Technology, UWE Bristol. The studentship will be funded by UWE Bristol and the Grey Walter Department of Neurophysiology at Southmead Hospital. Ref 2021-JAN-FET01.

The role is based UWE Bristol’s Health Tech Hub on Frenchay Campus.

The expected start date of this studentship is 1 October 2021.

The closing date for applications is Monday 31 May 2021

Studentship details

A fully-funded PhD studentship is available in the area of signal processing and artificial intelligence to monitor brain health. This exciting field aims to channel advances in computing power and techniques towards reducing the growing burden of neurodegenerative disease on our society. The successful candidate will be supported to develop their skills and international reputation as a researcher in artificial intelligence (AI) and data science for health applications.

Hospital neurophysiology departments provide vital diagnostic and prognostic information that informs the treatment of a wide range of conditions. Electroencephalography (EEG) is well established as a rich source of neurophysiological information. However, the extent of current use of EEG falls short of guidelines and its full potential, due to reliance on a limited number of trained neurophysiologists to interpret the data.

The aim of this project is to enable automated signal processing to extend the capabilities of our human neurophysiologists. A wide range of promising processing techniques and quantitative measures have been developed by the research community in recent years, but their clinical impact has been limited due to the challenges of working with real-world data rather than curated research datasets.

This project will give particular focus to the development of techniques to pre-process clinical data in order to improve the accuracy of emerging methods from fields such as deep learning and information theory, and to facilitate more efficient clinical workflows for neurophysiologists. The successful candidate may also contribute to the development and/or implementation of robust methods and infrastructure for responsibly handling clinical data for research purposes, in line with the NHS Long Term Plan’s objectives to expand the role of AI and digital technologies in the health service.

The project will form part of a broader collaborative research effort between the Grey Walter Neurophysiology Department and UWE Bristol. The primary objective is to benefit people with multiple sclerosis and other neurodegenerative diseases by developing accurate, efficient, and objective biomarkers of cognitive symptoms, which will lead to efficiency savings and accelerated drug development.

The successful candidate will work under the supervision of Dr David Western, along with Professor Richard McClatchey and Dr Kris Kinsey, at UWE Bristol’s Health Tech Hub. The Health Tech Hub is a friendly and dynamic inter-disciplinary research environment with expertise and state-of-the-art facilities to support investigations across the Health Tech spectrum, from atomic force microscopy and gene sequencing to smart home technologies.

The successful candidate will also work closely with colleagues at the Grey Walter Neurophysiology Department, which has a global reputation as a pioneer in the development of EEG and other modern neurophysiology techniques.

For an informal discussion about the studentship, please email Dr David Western at [Email Address Removed] or tel: +44(0)117 32 84986.


Eligibility

Essential

  • Undergraduate or Masters Degree (awarded at least 2:1 or equivalent) in a STEM subject (or equivalent work experience)
  • Experience programming in a language relevant to scientific computing, such as python or Matlab

Desirable

Background in any of the following:

  • Digital signal processing
  • EEG analysis
  • Designing, maintaining, or using large databases
  • Artificial intelligence

A recognised English language qualification is required.

How to apply

Please submit your application online. When prompted use the reference number 2021-JAN-FET01.

Supporting documentation: you will need to upload your research proposal, all your degree certificates and transcripts and your proof of English language proficiency as attachments to your application so please have these available when you complete the application form.

References: you will need to provide details of two referees as part of your application. At least one referee must be an academic referee from the institution that conferred your highest degree. Your referee will be asked for a reference at the time you submit your application, so please ensure that your nominated referees are willing and able to provide references within 14 days of your application being submitted. 

Closing date

The closing date for applications is Monday 31 May 2021.

Further information

Interviews will take place during the week commencing 21 June 2021. If you have not heard from us by Friday 18 June 2021, we thank you for your application but on this occasion you have not been successful.


Funding Notes

The studentship is available from 1 October 2021 for a period of three years, subject to satisfactory progress. It includes a tax-exempt stipend, which is currently £15,285 per annum.
In addition, full-time tuition fees will be covered for up to three years (Home/EU rates only). Overseas applicants will be required to cover the difference between Home/EU and the overseas tuition fee rates for each year of study.
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