PhD in Machine Learning & Medical Data Science

ETH Zurich; Zürich; On-site; CHF 60,000 - 80,000; Full time

Benefits offered by this job

International environment

Conference participation

Teaching experience

Research training

Job summary

ETH Zurich's Medical Data Science Group invites applications for a Doctoral Student in Machine Learning and Medical Data Science. You will conduct independent ML/AI research at the intersection of medicine and computing, developing methods with real healthcare impact.

Research topics include representation learning, foundation models, explainability, time-series and multimodal learning. You will publish, present, and contribute to teaching while pursuing your doctoral thesis.

Qualifications

• Master's degree in a technical field (CS/ML/Stats).
• Strong foundations in mathematics, statistics, and ML with Python programming.
• Interest in ML research and medical applications.
• Independent and systematic problem solving.
• Good English communication and interdisciplinary collaboration.

Responsibilities

• Conduct independent ML/AI research for medical applications.
• Design, implement, and evaluate ML models with rigorous experiments.
• Publish and present findings at conferences and journals; develop your thesis.
• Collaborate with technical and medical researchers and participate in group activities.
• Support teaching activities and supervision of student projects.

Skills

Python

ML research

Statistics

Mathematics

English communication

Interdisciplinary collaboration

Education

Master's degree in CS/ML/Stats

Tools

PyTorch

TensorFlow

Linux

Job description

ETH Zurich's Medical Data Science Group invites applications for a Doctoral Student in Machine Learning and Medical Data Science. You will conduct independent ML/AI research at the intersection of medicine and computing, developing methods with real healthcare impact.

Research topics include representation learning, foundation models, explainability, time-series and multimodal learning. You will publish, present, and contribute to teaching while pursuing your doctoral thesis.