PhD in Machine Learning for Medicine

About the role

The PhD project focuses on developing machine learning methods that learn from multimodal health data to characterize and model disease progression. You will work in the Machine Learning in Medicine Lab, collaborating with clinicians and an international research network.

Key responsibilities

• Develop multimodal representation learning approaches for imaging, time‑series and tabular health data.
• Model disease progression using cross‑sectional and sparse longitudinal datasets.
• Investigate causal machine learning to separate disease effects from treatment influences.
• Address challenges such as missing modalities, irregular sampling, and fairness across demographic groups.

Required profile

• Master's degree in a quantitative discipline (e.g., computer science, statistics, biomedical or electrical engineering).
• Strong foundation in machine learning theory and analytical skills.
• Motivation to conduct research in healthcare applications.

Required skills

• Python programming and experience implementing ML models.
• Familiarity with processing biomedical data (imaging, wearable sensor data, tabular clinical data) is a plus.

What we offer

• Fixed‑term contract (100%, 3 years) with a possible 1‑year extension.
• Annual gross salary of 50'042 CHF, including a 13th month.
• Strong research infrastructure, international network, and collaborative environment.
• Access to a vibrant medical AI community in Bern and a supportive work culture.