Job Description

Post-doctoral Research Scientist in Computational Modelling

Are you an ambitious researcher looking for your next challenge? Do you have a background in Medical Imaging, particularly in processing and modelling of microstructural / diffusion MRI? Do you want to further your career in one of the UK’s leading research-intensive Universities?

Cardiac Diffusion Magnetic Resonance Imaging (cDTI MRI) can measure the microstructure of the heart. Emerging data show the potential of cDTI in risk stratifying patients with heart disease and specifically in patients with aortic valve stenosis. This BHF-funded project, led by A/Prof Erica Dall’Armellina at the University of Leeds, aims to determine the robustness of cDTI in identifying microstructural changes in patients with aortic stenosis pre- and post-surgery. The post-holder will have a background in engineering, computing and/or image data analysis or equivalent and will be based in Leeds to support advanced data analysis and modelling on this project. Specifically, advanced imaging processing skills are essential to develop and validate algorithms for the combination of multiparametric / multi-scale images and extraction of quantitative information. The post-holder will also be required to travel to Manchester to work with collaborators (Prof. A. Frangi) as needed.

Responsibilities

• Support advanced data analysis and modelling for the cDTI MRI project.
• Develop and validate algorithms for combining multiparametric / multi-scale images and extracting quantitative information.
• Collaborate with internal and external partners to advance imaging processing techniques.
• Travel to Manchester to work with collaborators as required.

Qualifications

• Background in engineering, computing and/or image data analysis or equivalent.
• Experience in medical imaging processing, particularly diffusion MRI, and computational modelling.
• Ability to develop and validate algorithms for multiparametric imaging data.

What We Offer In Return

• 26 days holiday plus approx. 16 Bank Holidays (42 days per year).
• Generous pension scheme options plus life assurance.
• Health and wellbeing: discounted staff membership at The Edge campus gym.
• Personal development: access to courses run by our Organisational Development & Professional Learning team.
• All FMH staff are entitled to ten days staff development per year (pro rata).
• Access to on-site childcare, shopping discounts and travel schemes.

Contact

To explore the post further or for any queries, please contact:

Dr Erica Dall'Armellina, Senior Lecturer

Email: E.DallArmellina@leeds.ac.uk

Referrals increase your chances of interviewing at University of Leeds. Get notified about new Postdoctoral Researcher jobs in Leeds, England, United Kingdom.