PhD in AI, Diversity and Cardiology

We are looking for a PhD candidate to join the Dutch Heart Foundation-funded project DIVERSE-CVD. This research programme is a flagship collaboration between Amsterdam UMC, Erasmus MC and Radboudumc and focuses on improving cardiovascular risk prediction through diversity-aware artificial intelligence.

In this project, you will work with clinical datasets and large population biobanks containing electrocardiogram (ECG) data and cardiovascular outcomes. Your research will focus on developing and evaluating AI models that predict the onset and progression of atrial fibrillation, including post-operative atrial fibrillation, while accounting for population diversity.

Would you like to find out more about the various phases within the PhD trajectory? You can read more information on this page.

As a PhD candidate, you will contribute to the development of innovative AI methods for cardiovascular research and clinical practice. Your work includes:

• developing and implementing reusable data preprocessing pipelines for clinical and research data;
• transforming clinical data into research-ready datasets;
• developing and evaluating machine learning and deep learning models for diverse patient populations;
• improving model reproducibility through APIs, documentation and reusable workflows;
• publishing scientific articles and presenting research findings at national and international conferences.

You will collaborate closely with cardiologists, electrophysiologists, data scientists and researchers across participating institutions.

We are looking for an enthusiastic and communicative researcher who enjoys working in multidisciplinary teams and is eager to contribute to innovative cardiovascular research. You have:

• a completed master's degree in biomedical engineering, technical medicine, computer science, artificial intelligence or a related field;
• demonstrated affinity with cardiology or cardiovascular research;
• experience with Python and/or R;
• experience with cloud computing and/or Unix-based high-performance computing environments;
• strong organisational, communication and collaboration skills.