Framework for Open Hybrid Simulation and Analytics for Modelling Complex Systems in Health and Social Care
Applications are invited to join an exciting project on Hybrid Simulation. This fully funded doctoral project which aims to develop a Hybrid Simulation framework through establishing a hub for simulation and analytics tools (including licenced, open source, and freely available packages/software). The purpose of the framework is to inform decisions in health and social care systems tackling complex issues utilising available tools.
Start date1 April 2022
Funding sourceDoctoral College, University of Surrey
- Full UK tuition fee
- Stipend at £15,609 p.a. (2021/22)
- RTSG of £1,000 p.a.
- Personal Computer (provided by the department)
The rapidly rising complexity of health and social care systems (and the overall service sector) is reaching unpreceded levels. Problems such as congested emergency departments and obesity epidemic are common place now more than ever. Simulation Modelling is used in health and social care analytics to help decision makers understand the system and examine potential reactions to planned changes. There are three main Simulation approaches. These are Discrete Event Simulation (DES), System Dynamics (SD), and Agent Based Simulation (ABS). Hybrid Simulation (HS) is a term used to describe a model that is built based on linking two or more of these three approaches. The continuous rise in complexity in health and social systems gave led to significant increase in demand for HS recently, however, to realise the full its potentials, building HS models comes with several challenges. This research aims to tackle some of the challenges by developing a unifying framework to help modellers to link freely available simulation software in conjunction with a hub for sharing models and practices. The PhD candidate is expected to explore the possibility of developing a such framework. The research will include tasks such as review of uses of each approach and shortcomings; freely available tools and data; availability similar frameworks; and to develop a framework for linking models and library of models for use.
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 Masoud Fakhimi (Secondary Supervisor) is the chair of the main conference on Simulation in the UK and has also published widely in the field.
Applicants are expected to hold a good first degree (minimum 2:1) and a masters degree (minimum Merit) in a relevant subject from an internationally recognised university.
This studentship is available to UK students.
IELTS requirements: 6.5 or above (or equivalent) with 6.0 in each individual category.