JOB: Research Associate in Bayesian Statistics
School of Mathematics, Statistics and Physics, Newcastle University

Full advert: Research Associate in Bayesian Statistics Job Details | Newcastle University<https://jobs.ncl.ac.uk/job/Newcastle-Research-Associate-in-Bayesian-Statistics/1045949101/>

Applications are invited for a Research Associate position in Bayesian Statistics, for a period of 24 months.

The project is at the forefront of Bayesian inference and aims to design a novel Bayesian methodology to implement Bayesian Additive Regression Trees (BART) models to deal with non-linear phenomena. In particular, the aim is to bridge the Loss-based methodology to the framework of BART, building on the previous works of Prof Cristiano Villa and Prof Fabrizio Leisen on model selection, linear regression models and Gaussian graphical models.

The successful candidate will work on developing prior distributions to estimate the structure of the trees and the number of trees in a BART model, and building scalable and efficient computational tools to ease the implementation of the methodology.
The candidate must have a solid background in computational methods for Bayesian inference to develop efficient algorithms for the new proposed modelling framework. Within the project, the candidate will also perform theoretical modelling and data analysis, as well as disseminate the outputs through publications and presentations at scientific meetings.
The successful candidate will join the growing Statistics & Data Science group at Newcastle University and interact with the Statistics group at King's College London.

The position is offered on a fixed term basis for two years from the start date. Generous funds are available for travel, training and other support.
To apply, please complete the online application and attach a CV and covering letter. In your covering letter, please outline how you are either working towards, meet or exceed all the essential requirements for the role holder as outlined in the full advertisement, and highlight any expertise relevant to the described project.

For all information enquiries about the position, please contact Prof Kevin Wilson (kevin.wilson@newcastle.ac.uk), Prof Cristiano Villa (cristiano.villa@dukekunshan.edu.cn) or Prof Fabrizio Leisen (fabrizio.leisen@kcl.ac.uk).

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