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    Current vacancies


    PhD opportunity: Silent MR Imaging of the breathing Lung in Neonates

    Closing date: 15 April 2022

    Employer: The University of Sheffield 

    Location: Sheffield

    Apply now

    About the Project

    Supervisors: Dr. Neil J Stewart, Prof Jim M Wild

    Project details:

    There is a lack of robust, safe methods for imaging the lung structure and function in newborn babies. State-of-the-art magnetic resonance imaging (MRI) techniques show promise as a radiation-free alternative to computed tomography for imaging of lung structure, and can provide complementary information on lung function. However, MRI scanners produce significant acoustic noise (~ 100 dBA) that can cause patient discomfort, and traditional methods for dealing with respiratory motion during acquisition (e.g. breath-holding, respiratory bellows) are unfeasible in newborns.

    This project aims to address these shortcomings by developing novel “silent” free-breathing MRI methods with minimal acoustic noise, and tailored image reconstruction techniques incorporating model-based motion compensation.

    The student will simulate, program and test acquisition trajectories optimised for maximal scan efficiency and minimal acoustic noise, and will develop computational models of respiratory motion and lung physiology to produce a versatile image reconstruction software package. Developed methods will be evaluated in bespoke imaging phantoms and infants with lung developmental disorders, working with clinical collaborators at Sheffield Teaching Hospitals and Sheffield Children’s Hospital. The end goal is to achieve a silent MRI acquisition protocol and image reconstruction package for structural and functional lung assessment in neonates that can be performed during natural sleep.

    Specifically, the successful PhD student will undertake research in the following themes:

    • Magnetic resonance physics simulations and rapid, silent MR pulse sequence design
    • MR pulse programming on GE Healthcare scanners (C language)
    • Development of quantitative image analysis pipelines (Matlab, Python etc.)
    • Development of deep learning methods for lung image reconstruction and quantitative analysis
    • Investigation of imaging phenotypes of lung and cardiovascular disorders in infants

    This PhD project will be undertaken at the POLARIS (Pulmonary, Lung and Respiratory Imaging Sheffield) research laboratories. The student will have access to our 4 MRI scanners (at both clinically-used field strengths of 1.5T and 3T, including a newly-installed PET-MRI system), state-of-the-art hyperpolarisation and radiofrequency hardware laboratories, and the University of Sheffield high performance computing clusters.

    The student will also work closely with expert MR scientists at GE Healthcare on MRI acquisition method development.

    Upon completion of this PhD, the student will have a deep understanding of:

    • Magnetic resonance physics
    • Magnetic resonance pulse sequence programming
    • Image reconstruction and analysis algorithms
    • Deep learning
    • Lung and cardiovascular disorders in infants

    Entry Requirements:

    Candidates must have a first or upper second class honours degree in physics, (biomedical, electrical) engineering, computer science or related subject, or significant research experience.

    How to apply:

    Please complete a University Postgraduate Research Application form available here: www.shef.ac.uk/postgraduate/research/apply

    Please clearly state the prospective main supervisor in the respective box and select Department of Infection, Immunity & Cardiovascular Disease as the department.

    Enquiries:

    Interested candidates should in the first instance contact Dr Neil J Stewart (neil.stewart@sheffield.ac.uk)


    Funding Notes

    This studentship is funded by an EPSRC Doctoral Training Programme, including 3.5 years’ home fees + UKRI stipend (£16,062 per year for 2022/23).

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