From time to time vacancies arise within the department. Posts will be advertised on this page as and when they arise.
Research Associate in Monte Carlo Methods for Calibrating High-Dimensional Models
The post holder will be expected to conduct research in statistical methodology and Monte Carlo computations related to a project led by Dr Alexandros Beskos to develop and apply state-of-art Monte Carlo methods to calibrate complex high-dimensional models. Some main directions of intended research are; Multi-Level (ML) Sequential Monte Carlo (SMC) for Inverse Problems; Filtering for Stochastic Partial Differential Equations (SPDEs); Likelihood-Based Inference for Models with Memory.
Candidates should hold or be close to submitting a PhD (or equivalent qualification) in Statistics, or a closely related field. It is essential that the successful candidate has a strong background in Statistics / Computational Statistics, with previous experience of Bayesian theory and Monte Carlo algorithms, programming experience in statistical software packages e.g. R or Matlab and excellent communication skills.
The post is available from 1 October 2015 (or as soon as possible thereafter) and is funded for 12 months in the first instance.
Closing date: 31 May 2015
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Page last modified on 28 may 15 09:48