Postdoctoral Researcher in Cardiovascular Pharmacoepidemiology

More than 250,000 people in the Netherlands are living with heart failure, and this number continues to rise due to population ageing. For patients with heart failure with reduced ejection fraction (HFrEF), clinical guidelines recommend four cornerstone therapies, often referred to as the ‘fantastic four’. However, older adults frequently receive lower doses or fewer of these treatments than recommended because of factors such as frailty, multimorbidity, polypharmacy and concerns about treatment tolerability.

In this project, you will contribute to optimising and personalising heart failure treatment for older adults. You will apply advanced causal inference methods, including target trial emulation, to evaluate the effectiveness of different dosing strategies and combinations of guideline-recommended therapies in routine clinical practice. By leveraging linked national healthcare data, you will generate evidence for patient populations that are often underrepresented in randomised clinical trials.

As a postdoctoral researcher, you will work with large-scale linked datasets from hospitals, primary care, pharmacy records and national administrative databases. You will play a central role in designing and conducting target trial emulation studies and applying advanced epidemiological methods.

Your responsibilities include:

• designing, conducting and reporting target trial emulation studies using large-scale linked healthcare and administrative datasets;
• developing study protocols, statistical analysis plans and reproducible analytical workflows;
• applying advanced pharmacoepidemiological and causal inference methods;
• disseminating research findings through scientific publications, conference presentations and collaborative activities;
• supporting project coordination by working with project partners and contributing to project milestones and research outputs.

You are an independent and proactive researcher with a strong interest in causal inference in cardiovascular research. You enjoy working with complex healthcare data and translating scientific findings into clinically relevant insights.

You also have:

• a PhD in pharmacoepidemiology, epidemiology, pharmacology, biostatistics or a related field;
• extensive experience with statistical programming in R and analysing large observational healthcare datasets, preferably linked datasets;
• experience independently developing and conducting complex epidemiological analyses;
• demonstrated experience with pharmacoepidemiological and causal inference methods, including approaches to address confounding, selection bias and missing data;
• excellent scientific writing and communication skills and the ability to collaborate effectively across disciplines.