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PhD Studentship - Can artificial intelligence processing of clinical information optimise ambulance care of patients with suspected stroke


Population and Health Sciences Institute

Prof Chris Price Tuesday, April 20, 2021 Funded PhD Project (UK Students Only)
Newcastle United Kingdom Bioinformatics Epidemiology Neuroscience Operational Research Computer Science Mathematics Nursing & Health Statistics

About the Project

Number of awards

1

Start date and duration

September 2021 for 3 years full time.

Overview

The NIHR Applied Research Collaboration North East North Cumbria is offering a 3 year full time applied methodological (digital health science) doctoral fellowship hosted by the Newcastle University Stroke Research Group and the NIHR Newcastle MedTech and In vitro diagnostics Co-operative (MIC). 

The main purpose is to examine whether an artificial intelligence approach can combine information routinely collected during emergency ambulance assessment of patients with suspected stroke to improve the accuracy of clinical triage. Using data from previous clinical studies, further analysis will consider interactions between information routinely collected by ambulance practitioners and additional biomarkers, and examine whether identification of different patient subgroups can be enhanced by sophisticated integration of these different information sources. The intention is to build a more efficient clinical care pathway using information immediately available to ambulance practitioners.

The Applied Research Collaboration (ARC) for the North East and North Cumbria is one of 15 regional ARCS funded by the National Institute for Health research (NIHR).  

The Newcastle University Stroke Research Group is an established multidisciplinary team with a global reputation due to publications in high impact journals and presentations at key international scientific meetings. 

The NIHR Newcastle MIC is one of 11 centres across England generating high quality evidence that demonstrates the potential value of new medical tests, including advancing methodological approaches for the use of clinical and test data. The MIC methodologists have expertise in machine learning and related techniques. The team receive project funding from NIHR, Innovate UK and industry partners.

Sponsor

Newcastle University,  via the NIHR Applied Research Collaboration (ARC) North East and North Cumbria (NENC).

NIHR ARC NENC is one of 15 regional ARCS funded by the National Institute for Health research (NIHR) to bring together those needed to support research to improve health and care. Our vision is to deliver ‘better, fairer health and care at all ages and in all places’ through collaborative production and implementation of high quality applied health research in our seven themes. Our doctoral fellows are distributed across themes and universities according to the topic and required supervision. They are a crucial part of our ARC capacity building strategy.

Name of supervisor(s)

Chris Price (Lead)

Lisa Shaw

Clare Lendrem

Peter McMeekin (Northumbria University)

Eligibility Criteria

Candidates should be trained to Masters level in statistics, health informatics, digital health science or a related field, with an awareness of how artificial intelligence approaches can be used in a health care setting, particularly on a time-critical care pathway. The ideal candidate will have experience of working on health related projects, and also be able to independently engage with service providers (ambulance paramedics, doctors, nurses) to understand the most suitable algorithm content for integration with other aspects of care. Basic awareness of AI approaches to healthcare data processing is required, but training can be provided in the most relevant analsyis techniques.

If your first language is not English you need an overall IELTS score of 6.5 (at least 5.5 in all sub-skills) or equivalent language qualification.

This award is only open to home (UK) students.

 

How to apply

You must apply through the University’s online postgraduate application system by creating an account. To do this please select ‘How to Apply’ (https://bit.ly/2NLHpLa) and choose the ‘Apply now’ button.

All relevant fields should be completed, but fields marked with a red asterisk must be completed. The following information will help us to process your application. You should:

  • click on programme of study
  • insert 8300F in the programme code section and click search
  • select Programme name ‘PhD in the Faculty of Medical Sciences (full time) – Health Services Research’
  • insert PH018 in the studentship/partnership reference field
  • attach a covering letter and CV. The covering letter must state the title of the studentship. Please quote reference code PH018 and state in the covering letter how your interests and experience relate to the proposed project
  • attach degree transcripts* and certificates and, if English is not your first language, a copy of your English language qualification.

*You will not be able to submit your application until you have submitted your degree transcript/s.


Funding Notes

100% of home tuition fees paid and annual living expenses at UKRI rate (currently £15,609 per year). This award is only open to home (UK) students. A research training support grant of £5000 per year is available to cover research costs and local/national/international travel (conferences and exchanges).

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