Apply now: CLS PhD positions starting in 2027

In our highly competitive CLS doctoral training program, fellows are co-supervised by one advisor from ETH Zurich and one from the MPI for Intelligent Systems in Stuttgart / Tübingen, the MPI for Informatics in Saarbrücken or the ELLIS Institute Tübingen. Each CLS fellow has a primary location (chosen based on interests and match) and conducts a mandatory 12-month exchange at the other location. All CLS Ph.D. fellows register as graduate students at ETH Zurich and, upon successful completion of their Ph.D. project, will be granted a doctoral degree by ETH. Fellowships are fully funded. The program language is English. 
 
Faculty participating in this call (*only available as co-advisor for the one-year exchange): 
Zurich: Andreas Krause*, April Wang*, Benjamin Grewe, Celestine Mendler-Dünner, Christian Holz*, Daniel Razansky, Florian Dörfler, Gunnar Rätsch, Julia Vogt, Konrad Schindler, Marc Pollefeys, Menna El-Assady, Mrinmaya Sachan, Niao He, Quentin Boehler, Robert Katzschmann, Siddhartha Mishra, Siyu Tang, Stelian Coros.
Stuttgart/ Saarbrücken/ Tübingen: Alberto Comoretto, Antonia Georgopoulou, Antonio Orvieto*, Bernt Schiele, Bernhard Schölkopf, Buse Aktaş, Chelsea Rose Sidrane, Christian Theobalt, Jakob Macke, Jonas Geiping, Kashyap Chitta, Katherine Kuchenbecker, Konstantin Rusch, Maksym Andriushchenko, Maximilian Dax, Moritz Hardt, Philipp Müller, Rediet Abebe, Renate Sachse, Sahar Abdelnabi, Shiwei Liu.
 
Applicants should have a strong interest in doing basic research in areas such as:
AI for Science, AI Safety, Bio-inspired Robotics, Biomechanics, Causal Inference, Computational Biology, Computer Graphics, Computer Vision, Control Systems, Deep Learning, Digital Humans, Earth Observation, Educational Technology, Efficient AI, Explainable AI, Haptics, Human-Computer Interaction, Human-Robot Interaction, Imaging Technology, Machine Learning, Medical Informatics, Medical Robotics, Natural Language Processing, Neuroinformatics, Optimization, Physical AI, Probabilistic Models, Reinforcement Learning, Robotics, Security and Privacy, Smart Materials, Social Questions, Soft Robotics, Statistical Learning Theory, Visual Analytics.

Applicants must further hold or expect to hold an excellent degree at Masters level in a relevant subject. Good written and spoken English is essential. We value diversity at our institutions. If you feel that you meet our requirements, we encourage you to apply. 
 
Application
To join CLS in 2027, apply online. The application deadline for all parts of the application is midnight (23:59 CET) on November 2, 2026.
Long-listed applicants will be asked to submit a  2-5 minute research video.  Short-listed applicants will be invited to the CLS2027 Selection Symposium in Tübingen on March 1-2, 2027.