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MRC Biostatistics Unit- 6 funded PhD Opportunities
martes, 17 diciembre 2019

MRC Biostatistics Unit- 6 funded PhD Opportunities*
The BSU is an internationally recognised research unit specialising in statistical modelling with application to medical, biological or public health sciences.
We are currently recruiting for 4 (four) MRC funded BSU studentships and 2 (two) NIHR studentship.
To apply for any of the following PhD projects, please visit https://www.mrc-bsu.cam.ac.uk/training/phd/application-procedure/ .
Deadline for all application information to be received by the University application system is *Tuesday 7th January 2020*
All informal enquires to be directed to This e-mail address is being protected from spam bots, you need JavaScript enabled to view it
We currently have the following projects available at the MRC Biostatistics Unit.
• Data-adaptive approaches for causal inference– Stephen Burgess
• Modelling the association between blood pressure variability and cardiovascular disease– Jessica Barrett
• Bayesian dose adaptive trials using non-myopic response-adaptive methods – Sofia Villar and David Robertson
• Evidence synthesis in health impact models for interventions to prevent chronic diseases– Chris Jackson, Anne Presanis and Daniela De Angelis
• Accounting for heterogeneity in network neuroscience: extending the Bayesian Exponential Random Graph Model to infer and identify group differences– Simon White, Brian Tom and Brieuc Lehmann (University of Oxford)
• Conditional false discovery rates in high dimensional data sets– Chris Wallace
• Dynamic prediction of in-patient mortality based on electronic health record data: a comparison of landmarking and machine learning approaches– Steven Kiddle and Jessica Barrett
• Improving statistical methods for trial emulations using observational data– Li Su and Shaun Seaman
• Clinical prediction under informative presence: Exploring what the patterns and timing of repeated observations in routinely collected data can tell us about disease risk– Jessica Barrett and Brian Tom
• Statistical and machine learning analysis of images of platelet formation– William Astle and Cedric Ghevaert (University of Cambridge)
• Developing Bayesian non-myopic response-adaptive randomisation for the case of delayed endpoint observation – Sofia Villar and David Robertson
• Trajectories of modifiable risk factors and their influences on disease outcomes: using genetics in life course epidemiology– Stephen Burgess and Jessica Barrett
• Epidemic modelling with online model assessment: value of information and conflict– Anne Presanis, Chris Jackson and Daniela De Angelis
• Modelling the effect of gender on survival in cystic fibrosis patients– Jessica Barrett and Brian Tom
• How to detect changes in cognition trajectories: longitudinal study design to efficiently estimate biomarker change-point outcomes and time-to-change-point– Simon White and Brian Tom.