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PhD Studentship: Developing a hybrid simulation modelling approach to planning integrated care services

Loughborough University

Qualification Type: PhD
Location: Loughborough
Funding for: UK Students, EU Students, International Students
Funding amount: £15,009 per annum
Hours: Full Time
Placed On: 10th June 2019
Closes: 10th July 2019
Reference: SBE-ATSLR19
 

Application details:

Reference number: SBE-ATSLR19
Start date of studentship: 1 October 2019
Closing date of advert: 10 July 2019

Supervisors:

Primary supervisor: Dr Antuela Tako

Secondary supervisor: Professor Stewart Robinson

Short Introductory Paragraph

Applications are invited for an exciting, fully-funded three-year PhD research project in Healthcare Simulation modelling. You will work on a timely study that aims to support planning of community based integrated care services. We are looking for a quantitatively minded doctoral student who is interested in developing a hybrid modelling methodology and simulation tools, combining discrete-event simulation, system dynamics and agent-based modelling for use in healthcare planning. The findings of the study can inform NHS policy on the adoption of new integrated care models, giving you an opportunity to make real-world impact.

Loughborough University is a top-ten rated university in England for research intensity (REF2014). In choosing Loughborough for your research, you’ll work alongside academics who are leaders in the field of simulation as well as with healthcare practitioners and managers. You will benefit from comprehensive support and guidance from our Doctoral College, including tailored careers advice, to help you succeed in your research and future career.

Find out more: http://www.lboro.ac.uk/study/postgraduate/supporting-you/research/

Full Project Detail:

Providing efficient and effective community-based health and social care services requires careful planning. Analytical methods such as simulation can successfully support planning of health care services. The adoption of integrated care models is aimed at providing community-based health and social care services to the elderly population, while at the same time reducing A&E referrals. The project will develop a hybrid model of the integrated health and social care system for the UK elderly population, combining simulation techniques (system dynamics, discrete-event simulation and agent-based modelling) and problem structuring methods. The model developed will be used to answer questions regarding the capacity of integrated care services to efficiently meet current and future demand and to identify the resources needed.

Find out more:

http://www.lboro.ac.uk/departments/sbe/study/phd/

Skills and Entry requirements:

Strong quantitative background; a UK Masters degree ideally in Operational Research, Management Science, Business Analytics or a related subject (with average programme mark of no less than 65%) or International equivalent; interest in health care modelling; excellent communication skills; flexibility and willingness to travel. English Language requirement of IELTS band 7.0 or above with not less than 7.0 in each component.

Funding information:

The studentship provides a tax-free stipend of £15,009 per annum for the duration of the studentship plus tuition fees at the UK/EU rate. International (non-EU) students may apply however the total value of the studentship will be used towards the cost of the International tuition fee only.

Contact details:

Name: Dr Antuela Tako

Email address: A.Takou@lboro.ac.uk

Telephone number: +44 (0)1509 228219

How to apply:

All applications should be made online at http://www.lboro.ac.uk/study/apply/research/. Under programme name, select Business School.

Candidates are requested to submit:

  • - Application form;
  • - Curriculum vitae;
  • - Two academic references;
  • - Covering letter explaining your interest in, and aptitude for, the research project;
  • - A research proposal (2,000 word) based on the topic of the research project. This will be used to assess the students’ capability as a PhD researcher.

Please quote reference number: SBE-ATSLR19

   
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