Publisher
source

ETH Zurich

PhD Positions in Learning Systems, AI, Robotics, and Machine Learning at ETH Zurich and Max Planck Institutes ETH Zurich in Switzerland

Degree Level

PhD

Field of study

Computer Science

Funding

Fellowships are fully funded. PhD fellows register as graduate students at ETH Zurich and receive a doctoral degree from ETH upon completion. The program includes joint supervision and a mandatory 12-month exchange at the partner location.

Deadline

Nov 2, 2026

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Country

Switzerland

University

ETH Zurich

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Keywords

Computer Science
Biomedical Engineering
Electrical Engineering
Biology
Mathematics
Artificial Intelligence
Natural Language Processing
Computational Biology
Human-computer Interaction
Computer Vision
Probabilistic Modeling
Reinforcement Learning
Causal Inference
Human-robot Interaction
Optimisation
Robotics
Security And Privacy
Medical Robotic
ML

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About this position

PhD positions are open in the Max Planck ETH Center for Learning Systems (CLS), a highly competitive doctoral training program jointly connecting ETH Zurich with Max Planck partners in Stuttgart, Tübingen, Saarbrücken, and the ELLIS Institute Tübingen.

Successful fellows are co-supervised by one ETH Zurich advisor and one advisor from the Max Planck side, with a primary location chosen according to research fit. Each fellow completes a mandatory 12-month exchange at the partner location. All fellows register as graduate students at ETH Zurich and receive the doctoral degree from ETH upon completion.

The call spans a broad set of research interests in learning systems and AI, including 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, and visual analytics.

Eligibility highlights: applicants should have or expect to have an excellent Master's-level degree in a relevant subject, plus strong written and spoken English. The program is fully funded.

Faculty participating in the call include ETH Zurich researchers such as 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, and Stelian Coros, alongside Max Planck partners including 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, and Shiwei Liu.

Application deadline: November 2, 2026 at 23:59 CET. Long-listed applicants will be asked to submit a 2–5 minute research video, and short-listed applicants will be invited to the CLS2027 Selection Symposium in Tübingen on March 1–2, 2027.

Funding details

Fellowships are fully funded. PhD fellows register as graduate students at ETH Zurich and receive a doctoral degree from ETH upon completion. The program includes joint supervision and a mandatory 12-month exchange at the partner location.

What's required

Applicants should have a strong interest in 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, and Visual Analytics. Applicants must hold or expect to hold an excellent Master's-level degree in a relevant subject. Good written and spoken English is essential.

How to apply

Apply online through the CLS application portal. Submit all parts of the application by the deadline. Long-listed applicants will later be asked for a 2–5 minute research video, and short-listed applicants will be invited to the CLS2027 Selection Symposium in Tübingen.

More information can be found here

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