The National Institute of Health Research (NIHR) and Medical Research Council (MRC) will host a free symposium specifically designed for early-career methodologists. As well as talks on the future of methodology research from leading names in the field, there will also be interactive sessions and opportunities to network with (and seek advice from) fellow young methodologists and the funders themselves. The event will take place on 23rd September at the Grand Connaught Rooms, 61-63 Great Queen St, London, WC2B 5DA.
- “Communicating Research to a Non-Scientific Audience”
Professor Allan Gaw, NIHR-CRN,University of Leeds
- “The Evolution of Methodology Research and the Links Between the NIHR and MRC”
Professor Peter Brocklehurst, University College London
- “The Future of Clinical Trials Methodology”
Professor Max Parmar, University College London
- “Methodology for Stratified Medicine”
Dr Richard Emsley, The University of Manchester
- “Mathematical Modelling of Infectious Diseases”
Dr Daniela De Angelis, MRC Biostatistics Unit, Cambridge
- “Messy Data: Missing Data, Non-Compliance and Design Aspects of Trials”
Dr Ian White, MRC Biostatistics Unit, Cambridge
- “Tips for Writing Grant Applications”
Dr David Crosby, MRC Head Office
MRC Biostatistics Unit Programme Leaders invited speakers
Dr Daniela De Angelis – Programme Leader “ESH: Evidence Synthesis to Inform Health”.
Dr De Angelis’ research aims to develop and apply statistical methods to characterise epidemics, fully and correctly exploiting the complex body of available information on different aspects of the disease of interest. The goal of the research is to provide accurate and timely quantitative support to the implementation and evaluation of policies, particularly in the areas of HIV, hepatitis and influenza.
Dr Ian White – Programme Leader “DART: Design and Analysis of Randomised Trials”.
Dr White’s main biostatistics research areas are statistical methods for handling missing data and heterogeneity in meta-analyses. He works on finding methods that are well-grounded in statistical theory but which can be applied widely and conveniently in practice. This involves development of methods, writing user-friendly computer software, working with applied collaborators and disseminating good methods through short courses and tutorial articles.
Related documents – Downloads
- Speaker Biographies.pdf