Research Associate in Bayesian Statistics

3 weeks ago


Cambridge, Cambridgeshire, United Kingdom The International Society for Bayesian Analysis Full time
Research Associate in Bayesian Statistics and Causal Inference

We are seeking a highly skilled Research Associate to join our team at The International Society for Bayesian Analysis. The successful candidate will have a strong background in Bayesian and computational statistics or machine learning and causal inference, including machine and statistical causal structure learning.

The primary focus of this project is to develop novel causal inference tools tailored for single-cell sequencing data. This will involve working with large datasets, including the world's largest single-cell RNA-sequencing dataset of the human brain, to define molecular causes for neurological disease.

This is a collaborative project with national and international experts in their field, including Prof Michael Johnson, Professor of Neurology and Genomic Medicine, Imperial College, Dr Leonardo Bottolo, Reader in Statistics for Biomedicine, University of Cambridge, and Prof Guido Consonni, Professor of Statistics, Universita' Cattolica del Sacro Cuore, Milan, Italy.

The position is funded by the MRC Better Methods, Better Research panel and includes a generous travel and computing budget. The funds for this post are available initially for 3 years in the first instance.

As a Research Associate, you will have the opportunity to work on cutting-edge research and develop novel methodologies and software tools. You will also have the chance to collaborate with leading experts in the field and contribute to the advancement of Bayesian statistics and causal inference.

If you are a motivated and talented researcher with a passion for Bayesian statistics and causal inference, we encourage you to apply for this exciting opportunity.



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