The University of Sheffield
Research Associate in Digital Twins for Healthcare
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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
This is an exciting opportunity for a Research Associate from an engineering (systems, control or signal processing) or computer science (machine learning or data-driven modelling) background to support a major project at the intersection of systems engineering and healthcare delivery. You will work with a highly interdisciplinary research team and with our clinical and health data partners to ensure that systems engineering processes are applied to the reshaping of healthcare services. You will identify data analytics functions and digital twin requirements and develop software solutions integrating these components. You will have mathematical, modelling and computational skills, and be able to apply these in a dynamic and interdisciplinary research environment.
RESHAPE-CARE (re-engineering services for health, maximising person-centred care) is a research and innovation programme to transform care for people with multiple long-term conditions. It represents a partnership between systems engineers, healthcare researchers, health data experts and health service providers. It seeks to integrate the human (ensuring person-centred preferences about care) with the technological (“digital twin” computer models of health systems). The process of designing and implementing changes within services (general practices and community diagnostic centres) will follow systems engineering principles: an important part of this mixed methods researcher role is to participate in that process and also reflect and report on it. The project is underpinned by a strong commitment to Patient and Public Involvement and Engagement (PPIE) including people from underserved and under-represented communities.
RESHAPE-CARE is a partnership between the Universities of Sheffield (School of Medicine and Population Health and School of Electrical and Electronic Engineering) and Manchester with healthcare partners in South Yorkshire and Greater Manchester. It is jointly funded by the National Institute of Health Research and the Engineering and Physical Sciences Research Council.
Main Duties And Responsibilities
- Work with systems engineers and the model-based systems engineering model of the digital twin to build data-driven models of patients with multiple long-term conditions to the requirements.
- Work with relevant health datasets to pre-process time-series and other data to deal with missing information, synchronisation and any feature extraction to enable data-driven models to be built.
- Develop static and dynamic data-driven models using patient test and treatment data of multiple long term conditions patients using synthetic and real datasets.
- Contribute to the development of digital twins and data analytics functions working across data platforms and operating environments, coordinating with project partners and the research team.
- Conduct a comprehensive literature review to highlight state-of-the-art research in digital twins and its applications in healthcare.
- Prepare high quality papers for journals/presentations at technical level at national/international conferences and seminars for dissemination, and at a lay-person level to inform findings to multiple stakeholders.
- Report to supervisors and the wider project team on a regular basis about your research plan and results to discuss / agree any changes to the plan.
- Deliver project objectives assigned to your work package in a timely fashion, and coordinate with other work packages to ensure the solutions are integrated for the success of the whole project.
- Produce documentation of software, models and digital twin implementations and follow appropriate handover protocols.
- Plan research effectively by continuously monitoring results; the unpredictability of research means that daily planning needs to accommodate new developments.
- Carry out other duties, commensurate with the grade and remit of the post
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As a Research Associate in Digital Twins for Healthcare, you will be responsible for working with the lead investigators to deliver the patient and population digital twins. This will involve working with stakeholders (public and services) and academics from engineering, data science and health. The engineering focus of RESHAPE-CARE will involve you working with relevant health datasets and services for diabetes and breathlessness as part of the management of people with multiple long-term conditions, and developing digital twins based solutions.
You will work, within an agile management framework, on a work package dedicated to the digital twins development. It will have a work-package or task-related team comprising investigators, researcher colleagues and experts by lived experience. You will also be a full member of the wider RESHAPE-CARE research team and be expected to share your work and its findings across the work packages. This means you will have to work with people from different backgrounds and academic disciplines. You will have project management and secretarial support from members of our professional services team.
You will use your data-driven modelling skills to develop the digital twins by working with the project partners. Experience of working with heterogeneous and complex data and/or health data would be valuable. You will apply software engineering skills to the development of data-driven models and digital twin based software solutions and deploy them as services. You will be responsible for producing software documentation and technical reports, as well as regular reports of your work in formats that are accessible to the team, including those from different disciplines.
You will be based in the School of Electrical and Electronic Engineering and work closely with colleagues in School of Health and Related Research (the buildings are only a short distance from each other). You will be required to visit the project partners and healthcare providers (GP practices and diagnostic centres in South Yorkshire, Manchester.
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. Please ensure that you reference the application criteria in the application statement when you apply.
Criteria
Essential Or Desirable
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Stage(s) assessed at
- A PhD, or close to completion (or equivalent experience) in engineering (systems, control or signal processing), computer science (machine learning or data-driven modelling) or a related discipline.
Essential
Application
- Demonstrable experience of data-driven modelling.
Essential
Application/Interview
- Demonstrable knowledge of modelling dynamical systems from time-series data.
Essential
Application/interview
- Demonstrable ability to work with large and complex datasets.
Essential
Application/interview
- Demonstrable understanding/experience of working with health data.
Desirable
Application/interview
- Demonstrable ability to work flexibly across data platforms and operating environments.
Essential
Application/interview
- Demonstrable experience of developing software in Matlab, C++ or Python
Essential
Application
- Demonstrable writing skills including both academic papers and reports for other internal and external purposes
Essential
Application/Interview
- Excellent communication skills including managing meetings, making presentations and effective 1:1 communication
Essential
Application/Interview
- Demonstrable ability to work effectively with people from different disciplines
Essential
Application/Interview
- Demonstrable ability to work independently, plan own workload and prioritise conflicting deadlines
Essential
Application/Interview
- Demonstrable ability to apply creative approaches to solving complex technical problems
Essential
Application/Interview
Further Information
Grade
7
Salary
£38,784 - £41,064
Work arrangement
Full time (100% FTE, 35 hours per week)
Duration
41 months with an end date no later than 31 January 2030
Line manager
Professor Visakan Kadirkamanathan
Our website
https://www.sheffield.ac.uk/eee
For informal enquiries about this job, contact Professor Visakan Kadirkamanathan on visakan@sheffield.ac.uk.
Next steps in the recruitment process
It is anticipated that the selection process will take place in September 2026. This will consist of an interview and a presentation. We plan to let candidates know if they have progressed to the selection stage on the week commencing 23/07/2026. If you need any support, equipment or adjustments to enable you to participate in any element of the recruitment process, you can contact eee-operations@sheffield.ac.uk.
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 / Professional Services Shared Skills Framework.
- A range of generous family-friendly policies
- paid time off for parenting and caring emergencies
- support for those going through
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