Calling PhDs / Postdocs for Visiting Fellowships in Machine Learning at Newcastle University

Newcastle University is seeking enthusiastic early career researchers working in Machine Learning for fully-funded visiting fellowships hosted in the team led by Prof Chris Oates.

In this second call we aim to award 3 fellowships, and applicants may be from the UK or abroad.  A fellowship would typically last around 4-6 weeks, and should be carried out within one year of the award.  Permissible travel and accommodation expenses will be reimbursed up to £4,000.

Examples of some relevant research areas include:  Bayesian computation, Gaussian processes, generalised Bayesian inference, kernel methods, mean field Langevin dynamics, Monte Carlo, post-Bayesian inference, probabilistic numerics, and Stein's method.

To apply for a visiting fellowship, please prepare at most one page of A4 outlining:

• the proposed research project;

• potential collaborators at Newcastle;

• any accessibility requirements;

• whether approval from the home institution / supervisor has been sought.

Informal enquiries and formal proposals should be sent to chris.oates@ncl.ac.uk, with the closing date of 31 March 2026.  Successful applicants will be notified by 7 April 2026. 

All visiting fellowships are financially supported by the Leverhulme Trust.

Successful projects led by our Visiting Fellows in 2025

Clémentine Chazal, ENSAE. A Computable Measure of Suboptimality for Entropy-Regularised Variational Objectives. [arXiv]

Hudson Chen, University College London. Stationary MMD Points for Cubature. [arXiv]

Disha Hegde, University of Southampton. Automatic Selection of the Nugget for Linear System Solves in Machine Learning.