Senior Research Associate at Lancaster University, UK
Aug 3, 2017 Senior Research Associate in Non-Reversible MCMC Mathematics & Statistics, Lancaster University Salary: £32,958 to £38,183 Closing Date: Monday 18 September 2017 Interview Date: To be confirmed Reference: A1924 To apply:
Apply Here Informal inquiries to be addressed to Dr Chris Sherlock (c.sherlock@lancaster.ac.uk). A Senior Research Associate position for up to three years is dedicated to developing new methodologies in non-reversible Markov chain Monte Carlo (MCMC) and is led by Dr Chris Sherlock. 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 analyze them, both by simulation and theoretically. 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 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. We welcome applications from people in all diversity groups.
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Aug 3, 2017 Senior Research Associate in Non-Reversible MCMC Mathematics & Statistics, Lancaster University Salary: £32,958 to £38,183 Closing Date: Monday 18 September 2017 Interview Date: To be confirmed Reference: A1924 To apply:
Apply Here Informal inquiries to be addressed to Dr Chris Sherlock (c.sherlock@lancaster.ac.uk). A Senior Research Associate position for up to three years is dedicated to developing new methodologies in non-reversible Markov chain Monte Carlo (MCMC) and is led by Dr Chris Sherlock. 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 analyze them, both by simulation and theoretically. 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 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. We welcome applications from people in all diversity groups.
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