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Research Associate (Fixed Term)

Closing date: 
Sunday, 25 June 2023

MRC Biostatistics Unit

This is an exciting opportunity for an ambitious post-doctoral research associate to join the MRC Biostatistics Unit to carry out methodological research relating to Bayesian inference.

The post-holder will focus on developing novel Bayesian statistical methodology to improve the analysis and understanding of biomedical data, particularly relating to population health and/or patients in hospitals. Depending on their skills and interests, there are several potential directions that the postholder could pursue. These include (1) computational and/or methodological developments in Bayesian methods for model integration/data integration, such as building on ideas of Markov melding (https://doi.org/10.1214/18-BA1104 and https://doi.org/10.1007/s11222-022-10086-2) and chained Markov melding (https://doi.org/10.1214/22-BA1327); (2) improving methodology relating to prior specification (e.g. building on ideas in https://arxiv.org/abs/2303.08528); or (3) developing and implementing improved Bayesian methodology for handling large-scale multi-stream patient-level data extracted from modern hospital Electronic Health Record systems. The postholder will have the opportunity to take a central role in identifying and developing potential methodological developments, critically assessing and refining ideas for their ability to enable substantive biomedical questions to be answered more accurately or efficiently; and implementing and applying the proposed methodological developments to compare performance compared to existing approaches.

https://www.jobs.cam.ac.uk/job/41124/

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The Cambridge Centre for Data-Driven Discovery (C2D3) brings together researchers and expertise from across the academic departments and industry to drive research into the analysis, understanding and use of data science and AI. C2D3 is an Interdisciplinary Research Centre at the University of Cambridge.

  • Supports and connects the growing data science and AI research community 
  • Builds research capacity in data science and AI to tackle complex issues 
  • Drives new research challenges through collaborative research projects 
  • Promotes and provides opportunities for knowledge transfer 
  • Identifies and provides training courses for students, academics, industry and the third sector 
  • Serves as a gateway for external organisations 

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