Post Doctoral Research Assistant - Statistical or mathematical modeller - infectious disease transmission dynamics

Post Doctoral Research Assistant - Statistical or mathematical modeller - infectious disease transmission dynamics

2 Posts

Reference Number:PDRA-10-11

Category: Research, Science and Biotechnology

Salary: Kshs.240,148 – 305,536

Grade: 7.2 - 7.9

Location: Kilifi

Country: Kenya

Summary:

The Viral Epidemiology and Control (VEC) group at the KEMRI-Wellcome Trust Research Programme in Kilifi, Kenya is looking to appoint two individuals to investigate a set of questions relating to human respiratory virus transmission.

In particular this will focus on intra- and inter-virus species interactions, using individual and population level approaches and drawing from a wealth of community study data collected in Kilifi.

The successful candidates are likely to come from within the disciplines of statistics, physics, engineering, or applied mathematics and will have complementary statistical and mathematical skills in the use of transmission dynamic and statistical inference models.

Projects to include:

1. Viral interactions explored through deterministic multi-type transmission dynamic models.

Based on a RAS (realistic age-structured) compartmental model now set up in our group, develop a suite of models to investigate the transmission of multiple strains of a single virus species or multiple virus species, within age-structured populations. This will require inclusion of cross-immunity matrices, and should be generalised to "n" strains.

The model should, in the first instance, be used to regenerate the results of previous 2-strain modelling of respiratory syncytial virus and dynamic patterns of interacting viruses. Once the general framework has been developed the model can be used to explore a number of different hypotheses of interactions between viruses.

2. Estimation of parameters relating to competitive interactions between viruses from household repeated sampling data

Through the use of Bayesian MCMC modeling estimate rates of infection acquisition and recovery for and competition between viral variants or species using repeated measurement data from individuals within a household study.

Based on methods developed for pneumococcal and rotavirus type dynamic, investigate the hypothesis that respiratory viruses interact at the population level, and infer mechanisms of interaction and effects on different fitness qualities (such as infectivity, and shedding duration and level.)

Reporting Lines:

The post holder will report to Study PI

Education, Skills and Experience

Essential:

• PhD in mathematical or statistical modelling with a high numerical and computational content
• Evidence of ability to work independently
• Team player with excellent communication skills
• Enthusiasm to apply skills to the study of infectious diseases

Desirable:

• 2-5 year post-doctoral experience in a relevant area
• Experience in modelling directly applicable to the above projects
• Expertise in any of Matlab, R, STATA, WinBugs or similar
• Competence and interest to supervise at PhD / RA level
• Flexibility to spend time overseas with collaborators
• Experience of working in a developing country
• Strong publication record (e.g. ³ 1 first author peer-reviewed paper per year since PhD )

We particularly wish to encourage candidates with a fervent desire to develop a career in research in the East African Region.

Application procedure

To apply for this post you must be a registered user. Log into your account here then go to Vacancies, view the post and click on the button: "Apply for this job".

Please attach also a full academic CV and covering letter describing why you wish to be considered for one of these positions, together with your career aspirations.

Candidates must supply an email and telephone contact that will be used when offering interviews. The application closing date is 7th November 2011. Only shortlisted candidates will be contacted.

For further information on the appointments contact James Nokes (jnokes@kilifi.kemri-wellcome.org) and/ or Graham Medley (graham.medley@warwick.ac.uk).