PhD Studentship: Robust Bayesian Experimental Design and Inference

Overview

The School of Mathematics at the University of Birmingham is offering a PhD studentship on robust Bayesian experimental design and inference. Statistical methods are used across science to plan data collection (experimental design), draw conclusions from sparse and noisy data (inference) and assess uncertainty about those conclusions. Bayesian methods are increasingly common and have appealing theoretical guarantees when certain assumptions hold, but it is difficult or impossible to check in practice whether those assumptions are met.

The successful candidate will carry out a statistics and data science project aimed at understanding what happens to Bayesian methods when core assumptions are violated, and developing methods to reduce the consequences. There is particular emphasis on applications from psychology, cognitive science and computer science, and the student is encouraged to collaborate and communicate across disciplines.

Requirements

The university is looking for candidates with a background in, or a demonstrated ability to learn about, Bayesian methods, probabilistic machine learning or inverse modelling.

What you get

The scholarship covers home tuition fees, training support and a stipend at standard rates for 3 to 3.5 years.

Who can apply

Self-funded students from anywhere in the world are welcome to apply.

Key dates

The closing date is 4 December 2026.