Modelling measles transmission risk in adults SUPERVISORY TEAM Supervisor Dr Alexis Robert at LSHTMFaculty of...

Clinicians increasingly rely on prediction models to guide treatment choices. Most prediction models, however, are developed using observational data that include some patients who have already receiv...

Do you want to work on challenging problems within causal inference and contribute to algorithms that support treatment decisions for individual patients? As PhD candidate causal machine learning at t...

Large scale observational data are increasingly available for healthcare research, including from electronic health records and disease registries. Target trial emulation (TTE) provides a framework

Bayesian models offer a powerful framework for meta-analysis through their flexible and probabilistic treatment of uncertainty.There are several methodological challenges in evidence synthesis,

Dr Heejun Shin and Michael Cork will explore some essential methods for researching health problems associated with air pollution.

Job title: Four year postdoc position at the Oslo Centre for Biostatistics and Epidemiology (OCBE) (272144), Employer: University of Oslo, Deadline: Friday, January 31, 2025

The Centre for Data and Statistical Science for Health brings together data science expertise from across LSHTM to generate new opportunities for research, training and knowledge exchange into policy ...

In this postdoc position at LUMC, you will work on groundbreaking research that enhances the transparency and trustworthiness of decision support algorithms in healthcare. This position allows you to ...

Marginal structural models (MSMs) are often used to estimate causal effects of treatments on survival time outcomes from observational data when time-dependent confounding may be present. They can be...