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Pre-PhD Intern (Data Synthesis via Statistical Modelling)

Date Posted: Oct 05, 2020

Job Description

MLW is looking to recruit a Pre-PhD Intern to work on a project to develop statistical tools for synthesis and joint analysis of datasets from multiple studies with related study designs.

Streptococcus pneumoniae (pneumococcus) is the most common bacterial cause of pneumonia, meningitis and otitis media world-wide and antibiotic resistance among clinical isolates is rising. Liverpool School of Tropical Medicine (LSTM) have an established programme of work that examines immunological responses to controlled human infection (or experimental human pneumococcal challenge, EHPC) with pneumococcus as a platform to better understand the pathophysiology of disease and test potential, improved vaccines.

MLW is integrating datasets from EHPC studies into a database. Eventually, this database will incorporate past, current and future EHPC studies. We aim to develop statistical methodology to identify putative mechanisms that confer protection against pneumococcal colonisation and invasive disease. Further we hope to use this statistical methodology to inform optimal experimental designs for future EHPC studies.

This database of curated EHPC data will facilitate more extensive and ambitious modelling approaches and contribute to identifying combinations of protection mechanisms in different populations. Such insights could, in-turn inform vaccine development. Crucially, the database will allow integrative analyses of the experimental data. Individual studies were designed to study the effect of specific pathogen or patient characteristics. Indeed, while multiple protective mechanisms have been identified, none have been shown to be sufficient on their own.

The methods for building models using multiple, partially overlapping and heterogenous datasets that we hope to develop will be transferable to other datasets. While deeper statistical analysis of existing samples can lead to novel discoveries, a secondary objective is to identify gaps in the current EHPC data to improve the design of the future.

Position: Pre-PhD Intern (Data Synthesis via Statistical Modelling)

We wish to recruit a recent graduate with an MSc degree in Statistics (or related field) to develop integrative modelling approaches for a subset of the EHPC data. The internship will run for 12 months and is milestone managed with a review (centered on the candidate’s progress and feasibility of the modelling project) at 6 months.

If the project is successful, there is a possibility for the candidate to progress this research to a PhD in Biostatistics.

The successful candidate is expected to have a solid foundation in statistical theory, have previous experience in statistical modelling and be competent in at least one statistical programming environment, such as R.

The successful candidate will be working within the Statistical Support Unit at MLW, under the supervision of Dr. Marc Henrion, but also be attached to the Lung Health research group at MLW. Co-supervisors are the data custodians Prof. Daniela Ferreira and Prof. Stephen Gordon, with Dr. Ben Morton as an advisor.

How to apply

Interested candidate should send their applications (a covering letter and a 2-page CV) by email to:

Email: mhenrion@mlw.mw  and carbon-copy (cc)- Email:  training@mlw.mw  

mentioning ‘MARVELS EHPC statistical modelling intern’ in the subject line.

Deadline for applications is 11:59pm on Friday 16th October 2020 with the successful candidate to start in November 2020.

For informal enquiries, prospective candidates should contact Dr. Marc Henrion from the Statistical Support Unit at MLW:

Email: mhenrion@mlw.mw

Skills Required

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