Dr A Duncan
No more applications being accepted
Funded PhD Project (European/UK Students Only)
About the Project
A 3.5 year full time PhD position is available in the Probability and Statistics Group in the Department of Mathematics at the University of Sussex.
Monte Carlo Methods such as MCMC and SMC have played a key role in the application of Bayesian methods to real-world problems. These methods are typically based upon simulating discrete-time Markov processes. A number of recent developments in the last few years have given rise to a new class of MCMC methods which involve simulating a continuous-time piecewise deterministic Markov process (PDMP) that has been designed to be ergodic with respect to a given target posterior density. Numerical simulations suggest that these novel methods can provide a highly efficient alternative to standard MCMC methods for certain classes of posterior density.
It is crucial that any such algorithm remains efficient under increasing dimensionality. The aim of this project is thus to understand the scalability of PDMP based methods for sampling distributions on high dimensional parameter spaces. In particular, by identifying appropriate high-dimensional scaling limits for this class of process, we seek to understand the influence of hyperparameters (such as refreshment rate, reflection kernel etc) on the performance of the sampler in high dimensions. This PhD project includes components that pull on Statistics, Probability and Numerical Analysis and is at the intersection of these three disciplines. It is also anticipated that this project will enable the student to enhance valuable programming skills.
The student will work closely with their supervisor Dr. A. Duncan at the University of Sussex as part of an ongoing collaboration with Dr. J. Bierkens within the Delft Institute of Applied Mathematics at TU Delft.
Award Amount
Funded studentships cover a tax-free bursary (£14,553 per annum in 2017/18) and home/EU fee waiver for 3.5 years, as well as funding for research training and travel of £1650 per annum.
Eligibility
For this studentship, we are looking for a graduate in mathematics, statistics or a related discipline. Prior experience in statistical programming is desired but not required. Non UK applicants will also need to demonstrate IELTS qualification with 6.5 overall and not less than 6.0 in each section (or equivalent.) Please note that applications are welcome from non-UK applicants who are able to provide additional funding for the overseas fees.
Procedure
Apply on-line via the University of Sussex portal, http://www.sussex.ac.uk/study/phd/apply.
Applications should include a CV, as well as transcripts of marks obtained on your degree(s) and the details of two academic referees.
Due to the large volume of applications that we receive, we regret we may only contact you if your application is successful.
Timetable
Early application is advised. The studentship will be allocated as soon as a suitable candidate is found.
The deadline for applications is 1st December 2017. Shortlisted applicants will be informed as soon as possible after that date and will be required to undertake an interview.
The expected start date at Sussex is January 2018, with other start dates negotiable.
Further Information
This is a full-time studentship. With agreement of the supervisor the student may take on a limited amount of teaching, for which additional payment will be made.
Contact Details
Informal enquiries should be sent to Dr Andrew Duncan at [Email Address Removed]
Enquiries about your eligibility, the progress of your application and admission to Sussex, should be sent to Rebecca Foster [Email Address Removed]
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