PhD in Machine Learning in Medicine

About us

You will be supervised by Prof. Dr. Lisa Koch, head of the Machine Learning in Medicine Lab (www.mlm-lab.ch). Our research group develops trustworthy machine learning towards clinical use. Our methodological interests include uncertainty quantification, robustness and reliability, representation learning, probabilistic modelling, and causal machine learning, with applications in biomedical imaging, wearable and tabular data. We publish at leading machine learning and medical imaging venues, collaborate closely with clinicians at Inselspital, Bern University Hospital, and maintain close links to research groups across Switzerland and internationally.

We are a small and collaborative team and value regular interactions. Bern offers a strong and growing medical AI community and an excellent quality of life.

About the project

Chronic diseases often develop gradually over years, and their trajectories vary widely between individuals. Understanding this progression is key to early detection and timely intervention. Large multimodal health datasets combining medical imaging, wearable sensor data and clinical measurements now make it possible to study disease progression from multiple perspectives.

The goal of this project is to develop machine learning methods that learn from multimodal health data to characterise and model disease progression. Methodological focus areas the candidate may explore include:

• Multimodal representation learning across imaging, time series and tabular data
• Disease progression modelling from cross-sectional and sparse longitudinal data
• Causal machine learning to disentangle disease progression from treatment effects
• Learning with missing modalities and irregularly sampled signals
• Fairness and bias in multimodal models across demographic subgroups

The candidate

We are looking for a curious and motivated PhD candidate with a keen interest in doing machine learning research in the healthcare space. You should hold a Master's degree in a quantitative discipline such as computer science, machine learning, statistics, biomedical or electrical engineering, or similar. You have solid knowledge of the foundations of machine learning, are willing to dig deep to understand a problem, and have strong analytical skills. You have practical experience implementing and evaluating machine learning models in Python. Experience processing biomedical data (imaging, wearable, tabular) is a plus.