Effective algorithms for infectious diseases resource allocation applied to COVID-19 pandemic
Eligibility: UK/EU graduates with the required entry requirements
Reason for eligibility restriction: Funder requirement and timescale
Duration: Full-Time – between three and three and a half years fixed term
Application deadline: 14th August 2020
Interview date: Will be confirmed to shortlisted candidates
Start date: September 2020 or January 2021. Entry point will be subject to discussion and agreement.
For further details contact: Dr Seyed Mousavi
About the project
A common challenge in infectious diseases is how to allocate limited resources to manage the disease or control infection. For example, it would be important to know which population group to target with immunisation first, give masks and/or other diseases prevention products. While this may not be a problem in developed countries, it has been a growing problem in developing countries in Africa as witnessed with the HIV pandemic.
In this research, new algorithms are devised and implemented for the problem of allocating limited resources, such as vaccines, to control infectious diseases in general and COVID-19 pandemic in particular. Two important properties of the new algorithms are their accuracy, compared to existing algorithms, and their independence from the disease model, i.e. the mathematical model that describes the transmission dynamics of the disease. The latter is essential for COVID-19 and future potential infectious diseases because the epidemic model will change over the time as the result of extensive ongoing research on developing more accurate models. Most existing studies are limited to basic models such as the Susceptible Infected Recovered (SIR) model which are not adequate to capture characteristics of infectious disease such as COVID-19.
Full studentship which includes tuition fees and stipend for a doctoral candidate over 3.5 years.
The successful candidate will receive comprehensive research training including technical, personal and professional skills. All researchers at Coventry University (from PhD to Professor) are part of the Doctoral College and Centre for Research Capability and Development, which provides support with high-quality training and career development activities.
- A minimum of a 2:1 first degree in a relevant discipline/subject area with a minimum 60% mark in the project element or equivalent with a minimum 60% overall module average.
- A Masters’ degree in a relevant subject, or equivalent professional experience would be desirable.
- The potential to engage in innovative research and to complete the PhD within a 3.5 years.
- A minimum of English language proficiency (IELTS overall minimum score of 7.0 with a minimum of 6.5 in each component).
- The candidate should have a first degree in computer science or a very close discipline and be excellent at programming and algorithm design.
- Background in epidemic modelling and/or public health would be advantageous.
How to apply
All applications require full supporting documentation, a covering letter, plus a 2000-word supporting statement showing how the applicant’s expertise and interests are relevant to the project.Apply to Coventry University