Postdoc in Markov Chain Monte Carlo, Couplings, and Scalable Statistical Inference ESSEC Business School in France

ESSEC Business School is advertising a 1-year postdoctoral position starting in October in the area of statistics, probability, and Markov chain Monte Carlo (MCMC).

The position is connected to Pierre Jacob’s ERC project, “Markov Chain Monte Carlo using couplings toward scalable statistical inference” (UMCMC). The project focuses on improving MCMC methods through couplings, parallel computing, and modern computational approaches for scalable statistical inference.

Research themes mentioned in the project description include unbiased MCMC, adaptive and robust computation, numerical integration, probability approximation, Bayesian statistics, and applications involving latent-variable models, intractable likelihoods, knockoffs, distributions on graphs, and Bayesian nonparametric models.

This is a postdoctoral opening rather than a scholarship or degree programme. The post does not list a stipend amount, application deadline, or formal eligibility checklist, but it clearly seeks candidates with strong quantitative training and interest in statistical computation.

If you know a potential candidate, the announcer asks that you put them in touch.