Causal triangulation compares results from different study designs to help provided evidence for or against causation. We are looking for a PhD student to help us think through how this method can be better understood and applied.

Job description

Many key questions in epidemiology are fundamentally causal. Yet, we often have to rely on assumptions that cannot be directly verified to judge whether an observed association truly reflects causality. Causal triangulation offers a valuable tool to strengthen causal inference by comparing results from different study designs addressing the same question.

As part of this project, you will:

• Collaborate with our team to deepen the understanding of how causal triangulation works. This will rely heavily on causal inference but also formal reasoning and other methodological knowledge.
• In particular, this project will focus on how to quantitatively combine e...