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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.

We are seeking a Research Associate to join the School of Mechanical, Aerospace and Civil Engineering (MAC) 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 primarily driven by diabetes and hypertension. The VASCO-CKD project aims to develop the first clinically relevant, comprehensive computational model of renal haemodynamics and validate it using multi-scale human clinical data prospectively collected as part of the project.

As the successful candidate, you will lead the core computational modelling activities within Work Package 1 (WP1), under the direct supervision of Dr. Alberto Marzo. You will work closely with an interdisciplinary team, including a medical physics PDRA focused on clinical imaging data collection (WP2), alongside clinicians, MRI physicists 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 numerical modelling skills to make a real-world clinical impact on early disease prediction and personalized medicine.

Main duties and responsibilities

The postholder will lead the numerical model development and computational simulations within Work Package 1 (WP1). Key duties include:

• Lead the extension of Sheffield’s open-source 1D-0D whole-circulation solver (openBF) to incorporate detailed representations of renal macro- and microcirculation, glomerular filtration, and tubular reabsorption.
• Integrate intrinsic renal autoregulation mechanics (myogenic response, tubuloglomerular feedback) and extrinsic baroreflex feedback loops into the circulation framework.
• Construct explicit coupling methods to link the vascular models with state-of-the-art disease progression frameworks.
• Perform global sensitivity analyses (Sobol method) leveraging Gaussian process (GP) emulators to isolate sensitive parameters and optimize workflow computational costs.
• Calibrate and validate computational models against individual and population-level data generated in WP2, maintaining strict alignment with FDA and ASME V&V40 reliability guidelines.
• Generate UK-representative human virtual populations capturing demographic variations (age, sex, ethnicity) and varying stages of diabetic and hypertensive kidney disease.
• Deploy the virtual populations in simulated in silico clinical trials to identify robust non-invasive wave-derived biomarkers for early CKD detection and diagnosis.
• 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 experience doesn't match perfectly with this role's criteria, your contribution is valuable, and we encourage you to apply. Please ensure that you reference the application criteria in the application statement when you apply.

Further Information

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 modelling 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.

Our vision and strategic plan

We are the University of Sheffield. This is our vision: sheffield.ac.uk/vision (opens in new window).

What we offer

• 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.
• Generous pension scheme.
• 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
  • support for those going through the menopause
  • paid time off and support for fertility treatment
  • and more

More details can be found on our benefits page: sheffield.ac.uk/jobs/benefits (opens in a new window).

We are a Disability Confident Employer. 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.

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.