PhD – Mathematical and Computational Statistics – France

ESSEC Business School is offering a three-year PhD position as part of the ERC Consolidator Grant 101171415 – UMCMC (2025–2030): Markov Chain Monte Carlo using couplings towards scalable statistical inference, under the supervision ofPierre Jacob.

The project

This project develops Markov Chain Monte Carlo (MCMC) methods, in which Markov chains are generated to approximate a probability distribution of interest. The project is based on a framework known as unbiased Markov chain Monte Carlo (UMCMC), founded on Markov chain couplings and inspired by the parallel nature of modern computing architectures. This project develops UMCMC to harness its potential as a comprehensive foundation for probabilistic computation on modern hardware. This requires theoretical and methodological advances.

Broadly speaking, the project relates to statistics, probability, the Monte Carlo method, numerical methods, stochastic processes, Markov chains, couplings, optimal transport, robust statistics, differential geometry and reinforcement learning.

Proposed mission

The successful candidate will be part of a team led by the principal investigator. Postdoctoral researchers and other PhD students will also be involved (a total of four will be funded by the ERC project). The candidate will participate in all aspects of the scientific activities related to the project, including writing papers for publication in leading statistical journals, interacting with international collaborators, the possibility of extended stays abroad, attending conferences, etc.

This position will be based in Cergy (France), near Paris. The successful candidate will join a dynamic environment of researchers and lecturers in statistics at ESSEC Business School, with regular research seminars and teaching opportunities. Furthermore, they will benefit from the vibrant research environment of the Paris region, home to numerous universities and schools.