PDRA in MRI for Diabetes Assessment

1000scholars; Sheffield; On-site; GBP 38,000 - 52,000; Full time

Benefits offered by this job

Travel budget

Flexible working

Pension

41 days annual leave

Job summary

INSIGNEO Institute invites applications for a highly quantitative researcher to join the VASCO-CKD project in the School of Medicine and Population Health. You will develop MRI protocols for blood flow measurement and analyse clinical study data, linking MRI signals with computational vessel models.

Working with Dr. Alberto Marzo and Prof Steven Sourbron, you will contribute to advancing vascular imaging in chronic kidney disease, with a 42-month tenure and opportunities to travel to

Qualifications

• PhD-level researcher with strong MRI sequence programming skills.
• Experience with quantitative MRI methods and data analysis.
• Experience in phase-contrast MRI and 4D flow is advantageous.

Responsibilities

• Develop novel MRI protocols for blood flow measurement and analyse clinical study data.
• Integrate MRI results with computational models of the cardiovascular system.
• Collaborate with project leads and international partners to characterise vascular effects in kidney disease.

Skills

MRI sequence programming

Quantitative MRI

Phase-contrast MRI

4D flow

GE scanners

Education

PhD in a quantitative field

Tools

GE MRI 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.

Responsibilities

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.

Post Details & Benefits

• 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.
• travel budget funding international conference trips (such as the ISMRM or the Virtual Physiological Human Conference) during your 42-month tenure.
• highly competitive annual leave entitlement (41 days), a generous pension scheme, flexible working opportunities, and a strong commitment to your wellbeing.

Qualifications

• 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.

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.