Senior Research Associate in Non-Reversible MCMC

Lancaster University - Mathematics & Statistics

A Senior Research Associate position for up to three years, dedicated to developing new methodologies in non-reversible Markov chain Monte Carlo (MCMC) and led by Dr. Chris Sherlock is now available. In collaboration with Dr. Sherlock and members of the team at the National University of Singapore and the University of Glasgow, the postdoctoral researcher will develop new, efficient non-reversible algorithms, test and analyse them, both by simulation and theoretically, and implement them in an easy-to use package.

Most standard MCMC algorithms, such as the Metropolis Hastings algorithm, are reversible. However it is now well established that non-reversible MCMC algorithms can have substantially better mixing properties, particularly for the high-dimensional and complex models that are common in modern applications. Developing general purpose non-reversible MCMC algorithms is currently one of the most active areas of computational statistics.

A good understanding of standard, reversible MCMC is essential, as is a proven proficiency in computer programming.

Starting date: 1 November 2017 or a later date by arrangement.

Informal enquires can be addressed to Dr. Chris Sherlock (c.sherlock@lancaster.ac.uk).

We welcome applications from people in all diversity groups.

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Northern England