Doctoral Student in Machine Learning and Medical Data Science
ETH Zurich · Zurich
Description du poste
About the role
The Medical Data Science Group at ETH Zurich, led by Prof. Julia Vogt, is looking for a highly motivated Doctoral Student to join its interdisciplinary research team. The group develops machine learning and AI methods for medicine and healthcare, combining foundational advances with practical applications. Research directions include representation learning, foundation models, generative AI, explainability, probabilistic modeling, time-series analysis and multimodal learning. The position is fixed-term, based in Zurich.
Key responsibilities
- 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 findings at conferences and in peer-reviewed journals, and develop the doctoral thesis
- Collaborate with experts from technical and medical disciplines in seminars and group activities
- Support teaching activities and the supervision of student projects
Required profile
- Master's degree in computer science, machine learning, statistics, applied mathematics or a closely related technical field
- Strong interest in both foundational machine learning research and applications in medicine and healthcare
- Curiosity, creativity and independence in approaching research questions
- Strong analytical and problem-solving skills and commitment to rigorous scientific research
- Strong English and openness to interdisciplinary collaboration
- Experience with medical or biological data is an advantage but not required
Required skills
- Solid foundations in mathematics, statistics and machine learning
- Solid programming skills, for example Python
What we offer
- An international, collaborative research environment and access to high-performance computing resources at ETH Zurich
- Support for scientific development through conferences, training and networking
- Teaching, supervision and mentoring experience
- Competitive doctoral salary and employment conditions
- Benefits such as public transport season tickets, car sharing, sports, childcare and pension benefits
Applications are submitted online through the ETH Zurich application portal; the preferred deadline is 22 November 2026 and the preferred start date is 1 January 2027. Required documents: cover letter, CV, transcripts and degree certificates, contact details of three references, and a publication, thesis or summary.
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