PhD Fellowships in Learning Systems
Join a collaborative doctoral programme with joint supervision by ETH Zurich and Max Planck Institutes for cutting-edge research in AI and machine learning.
Best for:Best for recent or upcoming master’s graduates with a strong academic background in AI, machine learning, computer science, or related fields, seeking interdisciplinary research opportunities with joint supervision from top European institutions.
Overview
The Max Planck ETH Center for Learning Systems (CLS) offers fully funded PhD fellowships for outstanding candidates interested in foundational research across AI, machine learning, and related fields. Fellows will be co-supervised by advisors from ETH Zurich and Max Planck Institutes, with a mandatory 12-month exchange between locations. The programme grants a doctoral degree from ETH Zurich and provides unique interdisciplinary collaboration opportunities. Applicants should demonstrate a strong academic background in relevant disciplines and a passion for research in areas such as deep learning, robotics, or computational biology. The programme is conducted entirely in English and emphasizes diversity and inclusion.
What you'll do
- Conduct original research in a chosen subfield of machine learning, AI, or related disciplines under joint supervision from ETH Zurich and Max Planck Institutes.
- Develop and implement research projects with a focus on foundational contributions to learning systems.
- Participate in a mandatory 12-month exchange programme at the partner institution to foster interdisciplinary collaboration.
- Present research findings at conferences, workshops, and internal seminars.
- Collaborate with peers and supervisors to advance the field of learning systems through joint publications and knowledge exchange.
- Engage in teaching or mentoring activities as part of the doctoral training programme.
Requirements
Degree required: Master’s degree or equivalent in a relevant field such as computer science, machine learning, AI, robotics, or a closely related discipline; applicants expecting to complete their master’s by the start date are also eligible.
Degree offered: PhD
Language: English; excellent written and spoken proficiency is essential.
Instruction: English
- Strong academic background in machine learning, AI, or related fields.
- Excellent written and spoken English proficiency.
- Ability to conduct independent research and contribute original ideas.
- Experience with computational methods, programming (e.g., Python), and data analysis.
- Passion for interdisciplinary research and collaboration.
- Open to international applicants.
- No restrictions on nationality or residency.
- Applicants must hold or expect to hold a master’s degree by the start date.
Funding & terms
How to apply
Deadline: 2026-11-02 (CET)
Applicants must submit their application through the official CLS portal. Long-listed candidates will be asked to provide a 2-5 minute research video. Short-listed applicants will be invited to attend the CLS2027 Selection Symposium in Tübingen on March 1-2, 2027, where final selections will be made.
- CV
- Cover letter
- Academic transcripts (BSc and MSc)
- Two letters of recommendation
- Research video (2-5 minutes, for long-listed applicants)
- Proof of English proficiency (if not from an English-speaking institution)
Contact
CLS Application Office· Application Coordinator
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