PDRA in MRI for Diabetes assessment

Dunhillmedical; Sheffield; Híbrido; GBP 36.000 - 48.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Annual leave entitlement

Pensions scheme

Flexible working opportunities

Descripción de la vacante

The University of Sheffield seeks a Research Associate to lead core MRI activities within the VASCO-CKD project. You will develop MRI protocols, analyse phase-contrast data, and collaborate with engineers, clinicians, and researchers to advance in silico medicine.

This 42-month fixed-term post offers hybrid work, access to cutting-edge imaging resources, and opportunities to publish in top journals while contributing to personalized medicine.

Formación

• PhD (or near completion) in a highly quantitative field such as Physics, Engineering, Applied Mathematics, or Computational Biomedical Imaging.
• Documented experience in MRI sequence development and sequence programming.
• Strong background in MRI physics and processing and modelling of MRI data.
• Experience with open-source software and GitHub; open-science data sharing standards.
• Excellent communication and collaboration in multidisciplinary research settings.
• Track record of peer-reviewed publications or technical reports.
• Experience in setting up and analysing phase-contrast MRI data.
• Experience with GE scanners.

Responsabilidades

• Lead MRI protocol development and clinical studies within WP2.
• Retrospectively analyse renal phase-contrast data from EU-funded iBEAt study.
• Set up a novel MRI protocol on GE scanners to measure renal blood flow and velocity.
• Develop a data analysis pipeline and integrated database.
• Conduct a clinical study in 80 patients and healthy controls.
• Collaborate with various researchers to apply the model to data.
• Package data and models into open-access repositories (GitHub/Zenodo).
• Present milestones at meetings and conferences.

Conocimientos

MRI sequence development

MRI physics

GitHub/open science

Interdisciplinary collaboration

Educación

PhD in Physics/Engineering/Applied Mathematics/Computational Biomedical Imaging

Herramientas

GE scanners

Phase-contrast MRI data

Descripción del empleo

Job Title: PDRA in MRI for Diabetes assessment

Posting Start Date: 12/10/2026

Job Id: 3251

School/Department: School of Medicine & Population Health

Work Arrangement: Full Time (Hybrid)

Contract Type: Fixed-term

Closing Date: 09/11/2026

The University of Sheffield is a remarkable place to work. Our people are at the heart of everything we do. Their diverse backgrounds, abilities and beliefs make Sheffield a world-class university.

We offer a fantastic range of benefits including a highly competitive annual leave entitlement (with the ability to purchase more), a generous pensions scheme, flexible working opportunities, a commitment to your development and wellbeing, a wide range of retail discounts, and much more. Find out more about our benefits (opens in a new window) and join us to become part of something special.

Overview

We are seeking an enthusiastic Research Associate (Research Associate 2) to join the Medical Imaging Team in the Division of Clinical Medicine and the INSIGNEO Institute for in silico medicine at the University of Sheffield. This 42-month position is funded by the Engineering and Physical Sciences Research Council (EPSRC) as part of the pioneering project "Vascular Computational Modelling in Chronic Kidney Disease (VASCO-CKD)".

Chronic Kidney Disease (CKD) affects ~10% of the global population and is most often caused by diabetes and hypertension. The VASCO-CKD project will develop a non-invasive means of differentiating these two causes, which would offer significant opportunities to improve patient outcomes by tailored management. Our approach builds on a combination of comprehensive computational modelling of the cardiovascular system, informed by extensive blood flow measurements using phase-contrast MRI in patients and healthy controls.

As the successful candidate, you will lead the core MRI activities within Work Package 2 (WP2), under the direct supervision of Prof Steven Sourbron. You will work closely with an interdisciplinary team, including an engineering Research Associate focused on model development (WP1), alongside clinicians, engineers and established public and clinical stakeholder networks (WP3).

You will be embedded within the INSIGNEO Institute, Europe's largest in silico medicine institute, providing a world-class, multidisciplinary ecosystem of over 400 clinical and engineering researchers. This role provides an outstanding opportunity to leverage your MRI skills to make a real-world clinical impact on personalised medicine.

Main duties and responsibilities

The postholder will lead the MRI protocol development and clinical studies within Work Package 2 (WP2). Key duties include:

• Retrospectively analyse the renal phase contrast data from our EU-funded internation study iBEAt on diabetic kidney disease which includes data from over 500 patients with 4-year follow-up.
• Set up a novel extensive phase-contrast based MRI protocol on our GE scanners to measure renal blood flow and velocity at various points in the arterial trea, with an extra focus on renal vessels.
• Develop an integrated database and analysis pipeline for retrospective and prospective data.
• Set up and run a clinical study in 80 patients and healthy controls to provide extensive measurements that can inform the model development.
• Work with Research Associate 1 to apply the newly developed model directly to the data and use it to measure hidden model parameters.
• Support Research Associate 1 in the validation of the computational model, generation of virtual populations and development of in-silico clinical trials based..
• Package data, analysis pipelines, and documented models into a clean, open-access public repository hosted via GitHub and Zenodo under open Apache 2.0 and CC-BY 4.0 licensing.
• Maintain highly effective working relationships across the interdisciplinary team, presenting key milestones at monthly alignment meetings and international conferences.
• Carry out other duties, commensurate with the grade and remit of the post.

Person Specification

Our diverse community of staff and students recognises the unique abilities, backgrounds, and beliefs of all. We foster a culture where everyone feels they belong and is respected. Even if your past experience doesn't match perfectly with this role's criteria, your contribution is valuable, and we encourage you to apply.

Criteria

A PhD (or near completion/equivalent experience) in Physics, Engineering, Applied Mathematics, Computational Biomedical Imaging, or a related highly quantitative field.

Application

Documented experience in MRI sequence development and sequence programming.

Application/Interview

Strong background in MRI physics and processing and modelling of MRI data.

Application/Interview

Experience with open-source software codebases, version control (e.g., GitHub), and open-science data sharing standards.

Application

Effective communication and interpersonal skills, with a proven ability to collaborate in multi-disciplinary research environments.

Application/Interview

A track record of authoring high-quality peer-reviewed scientific publications or technical project reports.

Application

Experience in setting up and analysing phase contrast MRI data

Application/Interview

Experience with sequence development on GE scanners.

Further Information

Grade

Grade 7.3 – 7.6

Work arrangement

Full-time

Duration

Fixed-term for 42 months

Line manager

Professor in Medical Imaging Physics (Prof. Steven Sourbron)

Direct reports

Professor in Medical Imaging Physics (Prof. Steven Sourbron)

Right to work in the UK

If you do not currently hold the right to work in the UK, you can find more information here to help determine your visa eligibility. Additional guidance is also available on the UK Visa & Immigration website .

For informal enquiries about this job contact Prof. Steven Sourbron, Professor in Medical Imaging Physics: on [e-mail]

Next steps in the recruitment process

It is anticipated that the selection process will take place on a date to be confirmed following shortlisting. This will consist of a formal panel interview and a technical presentation outlining your previous computational modeling work. We plan to let candidates know if they have progressed to the selection stage shortly after the closing date. If you need any support, equipment or adjustments to enable you to participate in any element of the recruitment process you can contact the HR recruitment team.

• A minimum of 41 days annual leave including bank holiday and closure days (pro rata) with the ability to purchase more.
• Flexible working opportunities, including hybrid working for some roles.
• A wide range of discounts and rewards on shopping, eating out and travel.
• A variety of staff networks, providing opportunities for social interaction, peer support and personal development (for example, Race Equality, LGBT+, Women’s and Parent’s networks).
• Recognition Awards to reward staff who go above and beyond in their role.
• A commitment to your development access to learning and mentoring schemes; integrated with our Academic Career Pathways and the INSIGNEO Training Academy.
• A range of generous family-friendly policies
  • paid time off for parenting and caring emergencies
  • access to menopause support in the workplace
  • paid time off and support for fertility treatment
  • and more

We are a Disability Confident Leader (opens in a new window). If you have a disability and meet the essential criteria for this job you will be invited to take part in the next stage of the selection process.

Closing Date :09/11/2026

We are a research university with a global reputation for excellence. Our ideas and expertise change the world for the better, making a real difference to society. We know that when people come together with different views, approaches and insights it can lead to richer, more creative and innovative teaching and research and the highest levels of student experience. Our University Vision ( www.sheffield.ac.uk/vision ) outlines our commitment to building a diverse community of staff and students that recognises and values the abilities, backgrounds, beliefs and ways of living for everyone.

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Sheffield
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