PDRA in MRI for Diabetes Assessment

Independent; Sheffield; Hybrid; GBP 36,000 - 48,000; Full time

Benefits offered by this job

Dedicated travel budget for conference

Job summary

The University of Sheffield's INSIGNEO Institute invites a PhD-level researcher to develop MRI-based vascular modelling for CKD within the VASCO-CKD project. You will design protocols, run clinical studies and integrate MRI data with computational vascular models.

This 42-month post offers travel for conferences, collaboration across medical physics and engineering, and a supportive environment at INSIGNEO with access to global partners.

Qualifications

• PhD level (or near completion) in a highly quantitative field.
• Strong MRI sequence programming skills.
• Experience with phase-contrast MRI and 4D flow.
• Experience linking MRI data with computational vascular models.

Responsibilities

• Develop MRI protocols to measure blood flow.
• Run clinical studies and analyze imaging data.
• Integrate MRI signals with cardiovascular modelling.
• Collaborate with project leads and global partners.

Skills

MRI sequence programming

Quantitative MRI

Phase-contrast MRI

4D flow

GE scanners

Education

PhD in a highly quantitative field

Tools

GE scanners

Job description

Are you an ambitious researcher with a background in medical physics, engineering, applied mathematics, physics, or computational mechanics who wants to transform the future of medicine? We have an exciting opportunity in the School of Medicine and Population Health and the INSIGNEO Institute for in silico medicine for someone with a passion for medical imaging looking to use their skills to make a profound impact on chronic kidney disease patients.

You will join a well-connected, interdisciplinary team on the EPSRC-funded project "Vascular Computational Modelling in Chronic Kidney Disease (VASCO-CKD)". Chronic kidney disease affects approximately one in ten people, yet current tests only catch it in its late stages. Your work will lead the development of next-generation computational models to link visible changes seen in non-invasive medical scans with invisible microscopic vessel damage, laying the groundwork for early disease prediction, stratification, and digital twin design.

In this varied and dynamic role, you will be responsible for expanding developing novel MRI protocols for blood flow measurement, running clinical studies and analysing the data – integrating MRI sequence development with modelling of MRI signals and linking up with computational models of the cardiovascular system. Working alongside Project Lead Dr. Alberto Marzo and Prof Steven Sourbron, you will apply these methods in clinical studies using patients and matched volunteers to get the most extensive characterisation to data of vascular effects of diabetic and hypertensive kidney disease. You will also leverage an incredible ecosystem of global partners, medical physics researchers, and patient advocacy groups.

This post offers you an exceptional career move. You will be fully embedded in INSIGNEO, Europe's largest in silico medicine institute, boasting over 400 multidisciplinary members. To support your professional growth and global networking, this position includes a dedicated travel budget funding international conference trips (such as the ISMRM or the Virtual Physiological Human Conference) during your 42-month tenure.

Educated to PhD level (or near completion) in a highly quantitative field, you will possess strong MRI sequence programming skills and documented experience in quantitative MI. Experience in phase-contrast MRI, 4D flow and GE scanners would be a distinct advantage.

The University of Sheffield is a remarkable place to work. Our people are at the heart of everything we do. We offer a fantastic range of benefits including a highly competitive annual leave entitlement (41 days), a generous pension scheme, flexible working opportunities, and a strong commitment to your wellbeing.

We are committed to exploring flexible working opportunities which benefit the individual and University.

We build teams of people from different heritages and lifestyles from across the world, whose talent and contributions complement each other to greatest effect. We believe diversity in all its forms delivers greater impact through research, teaching and student experience.