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Patient-specific Analytics for Modelling Brain Tissue Perfusion During Heart Surgery Fellowship Program 2019, University of Leicester, UK

Publish Date: Apr 22, 2019

Deadline: May 06, 2019

Patient-specific analytics for modelling brain tissue perfusion during heart surgery

Qualification: PhD

Department: Cardiovascular Sciences

Start date: September 2019

Overview

This project is funded by the Medical Research Council (MRC) Integrated Midlands Partnership for Biomedical Training (IMPACT) Doctoral Training Partnership (DTP). It is also part of the Industrial Collaborative Awards in Science and Engineering (iCASE) studentship scheme.

Supervisors

Project Overview

This PhD project involves working with the paediatric cardiac surgery team and medical physics department within the University Hospitals of Leicester NHS Trust to record physiological measurements relating to the supply of oxygenated blood to the brain during paediatric congenital cardiac surgery. Recordings will include blood pressure, haematocrit, blood oxygenation, cerebral blood flow, and near infrared spectroscopy measurements. This information will inform the development of a prototype brain perfusion monitoring system capable of estimating brain tissue perfusion and oxygenation levels during heart surgery. The student will work with a data analytics company (Musoft) and UHL Clinical Engineering to develop their model into an NHS-ready prototype suitable for future clinical evaluation.

Supervisors

Dr. Emma Chung, University of Leicester, Department of Cardiovascular Sciences, emlc1@le.ac.uk 
Professor Antonio F. Corno, University of Leicester, Department of Cardiovascular Sciences, afc10@le.ac.uk 

Funding

Studentship provides tuition fees and stipend for 3.5 years to UK applicants. EU applicants who do not meet the RCUK residency criteria can apply for a fees only award.

For more information click "LINK TO ORIGINAL" below.


This opportunity has expired. It was originally published here:

https://le.ac.uk/study/research-degrees/funded-opportunities/chung-impact-case-2019

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Biology

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PhD

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