Enabling artificial intelligence for clinical neurophysiology
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 and Grey Walter Dept of Neurophysiology, Southmead Hospital, Ref 2021-JAN-FET01.
The expected start date of this studentship is 1 January 2021.
The closing date for applications is Monday 21 September 2020.
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.
Hospital neurophysiology departments provide vital diagnostic and prognostic information that informs the treatment of a wide range of conditions, including neurodegenerative diseases, traumatic brain injuries, stroke, and epilepsy. Electroencephalography (EEG; recording of the brain’s electrical activity) 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. Hence this project will give particular focus to the development of techniques to pre-process clinical data - including other sources such as magnetic resonance imaging (MRI) - 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 human neurophysiologists. To support this work, the successful candidate may also contribute to the development and/or implementation of robust modern 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 of this effort 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 at UWE Bristol’s Health Tech Hub, 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. Due to COVID-19, it is likely that the candidate will initially work remotely, but hopefully improvements in the pandemic situation will ultimately allow them to benefit from being physically located in the Health Tech Hub, as well as working closely with colleagues at Southmead Hospital’s Grey Walter Neurophysiology Department, which has a global reputation as a pioneer in the development of EEG and other modern neurophysiology techniques.
The studentship is available from 1 January 2021 for a period of three years, subject to satisfactory progress and 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 in each year of study.
- 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
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.
The closing date for applications is 21 September 2020.
Interviews will take place during the week commencing 14 October 2020. If you have not heard from us by 30 September 2020, we thank you for your application but on this occasion you have not been successful.