The Max Planck ETH Center for Learning Systems (CLS), a joint centre of ETH Zurich and the Max Planck Society, recruits doctoral fellows once a year for basic research in areas such as machine learning, computer vision and robotics.
Each fellow is co-supervised by an ETH Zurich advisor and one from the MPI for Intelligent Systems (Stuttgart/Tübingen), the MPI for Informatics (Saarbrücken) or the ELLIS Institute Tübingen, and earns an ETH Zurich doctorate.
Benefits & funding
- Fully funded: a contract at the same level as other PhD students in the host group; no amount is published, and pay changes with location (Germany or Switzerland).
- Standard length three years; a fourth year is possible in justified cases.
- A 12-month exchange at the co-advisor’s location is mandatory.
- Fellows pay ETH semester, registration, tuition and exam fees; CLS provides no housing.
Eligibility
- Open to all nationalities; no nationality or residence bar is stated.
- An excellent Master’s-level degree in a relevant field (e.g. computer science, physics, engineering, applied mathematics, neuroscience), held or completed by October of the year after applying and before the contract starts.
- Bachelor-only applicants, including ETH direct-doctorate students, are not eligible.
- Good written and spoken English; no certificate required, but other evidence of proficiency is.
- Interest in basic research in a CLS area.
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Application process
- 1Register on the CLS portal and choose advisors from those recruiting this round.
- 2Submit the form, degree certificates, transcripts, motivation letter and CV by 2 Nov 2026, 23:59 CET.
- 3Arrange 2–3 references from professors (not PhD students), submitted by the same deadline; late ones are refused.
- 4Long-listed applicants send a 2–5 minute research video.
- 5Short-listed applicants interview at the selection symposium in Tübingen.
Program timeline
Application and reference deadline
2 Nov 2026, 23:59 CET
Long-list asked for research video
Mid–late Nov 2026
Selection Symposium, Tübingen
1–2 Mar 2027
Flexible PhD start
Apr–Nov 2027