Thesis Work, 30 Credits: Negative-Binomial Recurrent-Event Trials

About the role

AstraZeneca is offering a thesis placement worth 30 credits, based on-site at AstraZeneca Gothenburg. The project investigates how follow-up duration and sample size can be optimised in clinical trials where patients may experience repeated events over time, using negative-binomial models. It is aimed at students enrolled in a Master's programme in statistics, mathematics or engineering.

Key responsibilities

• Evaluate how much additional value is gained by following patients for longer and when extended follow-up no longer provides meaningful benefit.
• Use statistical modelling and simulation to investigate different recruitment patterns and patient populations.
• Develop practical guidance for designing future recurrent-event clinical trials.
• Support the development of reliable and efficient trial designs while minimising patient burden and study resources.

Required profile

• Enrolled in a Master's programme in statistics, mathematics or engineering with a mathematical or statistical component.
• Interest in statistical modelling, clinical trials and biostatistics.
• Excellent English communication skills, including scientific writing and presentations.

Required skills

• Experience with programming, preferably in R.
• Basic knowledge of generalized linear models (GLMs) and experience with statistical simulation are advantageous.

The placement runs during Spring 2027. Applications are open until 29 October 2026, and the company reserves the right to close the vacancy early if suitable candidates are found.