Hybrid simulation as a vehicle for supporting primary and community health for reviewing consultation practices during pandemic and major crises

Applications are invited to join an exciting project on hybrid simulation to support health services during a pandemic (fully funded by NIHR: Applied Research Collaboration Kent, Surrey, and Sussex). This doctoral project aims at developing hybrid simulation models of real-life GP consultations to help healthcare systems recover from the impact of the pandemic by reviewing alternative decisions. Successful candidates will benefit from already established links to key healthcare networks.

Start date
1 April 2021
3/4 years
Application deadline
Funding information
  • Full UK/EU tuition fee covered
  • Stipend at £15,285 p.a. (2020/21)
  • RTSG of £1,000 p.a.
  • Personal Computer (provided by the department).
Funding source
NIHR: Applied Research Collaboration Kent, Surrey, and Sussex
Supervised by


The advent of COVID-19 has shaken the whole world to its core. Dedicating effort and resources to tackling the spread of the disease led to more pressure on Primary and Community Health Services leading to straining long-term conditions and health resources. Given the interconnectedness of the Primary and Community Health Services, in terms of system ownerships and multiplicity of decisions and impacts, Hybrid Simulation (HS), which connects systems’ models at micro, meso, and macro levels of the healthcare system, is a viable means for supporting decision makers. The purpose of HS is to assess the potential impacts of proposed ideas over time in simulated environments (digital twins) prior implementation. There are three main Simulation approaches, Discrete Event Simulation (DES), System Dynamics (SD), and Agent Based Simulation (ABS). HS is based on combining two or more of these approaches in a single model. Whilst, it is widely used for modelling secondary care systems, less work has been done to model Primary and Community Health Services. Therefore, this research aims at developing HS models of real-life GP consultations to help them recover from the impact of the pandemic. We are looking for a PhD candidate with technical expertise in Operational Research, Data Analytics, or Computing with interest in healthcare management to join an eclectic team in analytics and healthcare to fulfil the above project.

Dr Tillal Eldabi (Primary Supervisor) has published widely in the field of Hybrid Simulation and Analytics with seminal works in developing HS frameworks over the last 12 years. Dr Eldabi has will take the lead in providing the PhD candidate with the main topic of research.

Dr Carin Magnusson is a Lecturer in Health Services Research and have been doing research in the NHS for the last 20 years. She has a particular interest in patient safety and issues of governance and accountability across healthcare organisations.

Related links
Hybrid simulation modelling in operational research: A state-of-the-art review Applicability of hybrid simulation to different modes of governance in UK healt… Hybrid simulation for modelling large systems: an example of integrated care mo… NIHR ARC KSS

Eligibility criteria

Open to UK and EU students only.

The ideal candidate will hold an MSc degree in a relevant subject.

IELTS requirements: 7.0 overall with 6.5 in each band.

How to apply

All applicants are required to follow our online application process.

The application deadline is 12 February 2021. Shortlisted candidates will be invited to interview, which can be via Skype.

Please submit the following documents:

  • Curriculum Vitae
  • Evidence of English language proficiency (if English is not first language).
  • Research proposal (2 pages, based on PhD work description above)
  • Scanned passport copy
  • Scanned copies of signed/stamped qualifications/certificates or transcripts) to show how you meet (or expect to meet) the entry requirements
  • Contact details of 2 referees.

Additional information can be obtained from:

Application deadline

Contact details

Tillal Eldabi
27 MS 02
Telephone: +44 (0)1483 688755
E-mail: t.eldabi@surrey.ac.uk

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