PhD position in Statistics
Insight centre for Data Analytics, University College Dublin
in collaboration with the Alan Turing Institute, London.
Insight in collaboration with the Alan Turing Institute are seeking applications for a PhD in statistics and machine learning with applications in 3D-printing. This is an exciting project which will involve cutting-edge statistical and machine learning methodology motivated by a substantial problem in 3D-printing. The objective of this PhD project is to develop statistical methodology and models for the assessment of imperfections in 3D printed stainless steel, or more generally additively-manufactured metal components.
This project will be ideally suited to an applicant with a strong undergraduate (or Masters) degree in statistics, machine learning or a cognate area. The ideal applicant will also be required to have some experience in programming.
An exciting and key aspect of this PhD position is that it involves significant collaboration with the Alan Turing Institute. In particular this proposal is in collaboration with the data-centric engineering programme at the Turing Institute whose mission is to apply data-driven techniques to major engineering challenges, generating new research and working with industry to apply this research to real-world problems. This project will involve a secondment at the Alan Turing Institute for a total of one year over the course of the four year PhD programme, providing you with the opportunity to work in a world-class research environment in the heart of London.
This project will be supervised by Prof. Nial Friel (Insight), co-supervised by Dr. Chris Oates (Alan Turing Institute) and Prof. Mark Girolami (Alan Turing Institute).
Please apply by sending a CV including the names of two referees to Nial Friel ([log in to unmask]). Applications will be considered at any time until this post is filled, up to August 15th.
This is a 4 year fully funded PhD position, with a PhD scholarship of euro 18,500, tax-free per year. This scholarship will also cover PhD fees and provide substantial support for training and travel.
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