Senior Investigator Statistician at MRC Biostatistics Unit, Cambridge

Senior Research Statistician
MRC Biostatistics Unit
Cambridge
Fixed Term Post to 31st March 2019

This is an exciting opportunity for an ambitious Research Fellow to join the MRC Biostatistics Unit and the team led by Dr Daniela De Angelis to carry out research within the "Evidence synthesis for Health" theme. You will join an internationally renowned Biostatistics Unit and a team working at the cutting edge of development and application of Bayesian modelling to the synthesis of data from multiple sources. The overall aim of this research programme is to advance existing knowledge on evidence synthesis methodology while addressing substantive problems in infectious disease epidemiology and public health.

You will be an experienced statistician and will be expected to lead on a range of projects within the NIHR Health Protection Research Unit "Evaluation of Interventions" collaboration between the MRC BSU, Bristol University, UCL and Public Health England. Within this context, the work will particularly focus on the building of the evidence base needed to inform interventions. Current topics of interest include estimation of prevalence and incidence of blood-borne infections (e.g. hepatitis B and C) and the characterization and prediction of antimicrobial resistance. This work will involve the synthesis of data from multiple sources; of different types (e.g. epidemiological and genetic); at different levels of aggregation; and from biased observational studies and/or biased surveillance sources.

You will have a PhD in statistics, biostatistics or related discipline; experience of statistical packages (e.g. R); substantial experience of Bayesian statistics and of methods for synthesising multiple sources of evidence in complex probabilistic models. You will lead on a range of projects and play a major role in the strategic development of the research group, through the conduct of research, introduction of new ideas, dissemination of research results, and support and training of others. You must have good communication skills and be able to contribute substantially to writing scientific papers. This position is within the team led by Daniela De Angelis, but you will also work closely with the other teams within the Unit.

The MRC Biostatistics Unit aims to advance medical science by the development, application and dissemination of statistical methods. It is one of Europe's leading biostatistics research institutions and includes many internationally renowned statisticians. It provides a privileged environment for conducting research within the Cambridge biomedical environment.

Starting salary will be in the range of £36,657 - £43,089 per annum, supported by a flexible pay and reward policy, 30 days annual leave entitlement, and an optional MRC final salary Pension Scheme.

The MRC is a unique working environment where our researchers are rewarded by world class innovation and collaboration opportunities that the MRC name brings. Choosing to come to work at the MRC means that you will have access to a whole host of benefits from a final salary pension scheme and excellent holiday entitlement to access to employee shopping/travel discounts and salary sacrifice cycle to work scheme and childcare vouchers, as well as the chance to put the MRC on your CV in the future.

To apply, please visit our job board at http://www.mrc-bsu.cam.ac.uk/recruitment/current-vacancies/ complete an Application Form and forward your CV and cover letter to:
This email address is being protected from spambots. You need JavaScript enabled to view it., quoting Reference Number MRCBSU0003.

Closing date: 31st December 2015 Interview date: 15th January 2016

This position is subject to pre-employment screening The Medical Research Council is an Equal Opportunities Employer

This email may have a protective marking, for an explanation please see http://www.mrc.ac.uk/About/Informationandstandards/Documentmarking/index.htm

We use an electronic filing system. Please send electronic versions of documents, unless paper is specifically requested.