Doctoral Student in Machine Learning and Medical Data Science

Conduct independent research on novel machine learning and AI methods, with a focus on medical and healthcare applications Design, implement, and systematically evaluate machine learning models and experiments, ensuring rigorous and reproducible research Publish and present your findings at scientific conferences and in peer-reviewed journals, and develop your doctoral thesis Collaborate with experts from technical and medical disciplines and contribute to scientific discussions, seminars, and group activities Support teaching activities and the supervision of student projects

The Medical Data Science Group at ETH Zurich, led by Prof. Julia Vogt, is an interdisciplinary research team. The group develops innovative machine learning and AI methods to address challenging problems in medicine and healthcare. Its research combines foundational advances in machine learning with meaningful medical applications. Potential research directions include representation learning, pre- and post-training of foundation models, generative AI, explainability and interpretability, probabilistic modeling, time-series analysis, and multimodal learning. The doctoral position offers the opportunity to pursue original research at the intersection of machine learning and healthcare, working closely with researchers from technical and medical disciplines. Specific research topics will be developed jointly with Prof. Julia Vogt, taking into account the candidates' interests and expertise as well as the group's research priorities.

ETH Zurich is one of the world’s leading universities specialising in science and technology. It is renowned for its excellent education, cutting-edge fundamental research and direct transfer of new knowledge into society. Over 30,000 people from more than 120 countries find the university to be a place that promotes independent thinking and an environment that inspires excellence. Located in the heart of Europe, it forges connections all over the world and works to develop solutions for global challenges.

• A Master's degree in computer science, machine learning, statistics, applied mathematics, or a closely related technical field

• Strong foundations in mathematics, statistics, and machine learning, combined with solid programming skills (e.g., Python)

• A strong interest in both foundational machine learning research and applications in medicine and healthcare

• Curiosity, creativity, and the ability to approach challenging research questions independently and systematically

• Strong analytical and problem-solving skills, with a commitment to rigorous and responsible scientific research

• Strong communication skills in English and enthusiasm for interdisciplinary, collaborative research

• Openness to new ideas, constructive feedback, and scientific exchange

• Experience with medical or biological data is an advantage, but not a requirement