Postdoctoral Scientist – Machine Learning for Organoid Phenotyping

About the role

The ML for Biosystems Engineering group at Roche's Institute of Human Biology in Basel seeks a Postdoctoral Scientist to develop machine learning methods for organoid phenotyping and high‑throughput screening, supporting drug discovery with complex human model systems.

Key responsibilities

• Lead a research project developing computational methods for organoid engineering and drug discovery.
• Design and implement state‑of‑the‑art statistical and machine‑learning models on high‑content, multimodal datasets.
• Collaborate with experimental scientists to shape experiments and ensure translational impact.
• Publish research findings and contribute open‑source tools to the scientific community.

Required profile

• PhD in computational biology, computer science, machine learning, bioinformatics or related field.
• Track record of independent research demonstrated by publications, preprints or software contributions.
• Strong experience with statistical or machine‑learning methods applied to high‑dimensional biological data.
• Ability to work closely with experimental collaborators in an interdisciplinary environment.

Required skills

• Proficiency in Python.
• Experience with modern ML frameworks such as JAX, PyTorch or TensorFlow.
• Scientific programming practices including version control, testing and reproducible workflows.