Cambridge Centre for Research Associate in Machine Learning
MRC Biostatistics Unit
An exciting opportunity has arisen for a highly motivated and talented post-doctoral biostatistician, statistician or researcher in machine learning to join Dr Brian Tom's group at the MRC Biostatistics Unit, Cambridge University, to work on developing and applying methodology for estimating optimal treatment regimes to data arising from observational cohort studies, trials or electronic health records within the area of precision medicine.
The successful candidate will have a PhD in a strongly quantitative discipline, ideally statistics or statistical machine learning, with experience in one or more of the following areas: longitudinal data analysis, event history modelling, causal inference and statistical machine learning. Experience with biomedical or epidemiological applications would be highly advantageous, but not essential. A desire to develop methodology for tailoring treatment decision making (including understanding the theoretical underpinnings) and to address questions of substantive biomedical importance is essential. The ability to work as part of a multi-disciplinary team and to communicate clearly and effectively is important. Good statistical programming skills are required.