RobotX PhD Fellowship 2027
About the role
RobotX, the Center for Robotics at ETH Zurich, is looking for outstanding doctoral students who want to build robots that work in the real world. With the RobotX PhD Fellowship 2027, you apply once and are considered by several RobotX research groups across ETH Zurich. You choose up to three professors you would like to work with, and they review your application.
Application deadline: 27 November 2026.
Job description
The research groups of RobotX cover a broad spectrum of robotics, including but not limited to:
- Soft and Musculoskeletal Robotics: bioinspired robots built from compliant materials, artificial muscles, and tendons, for safe and adaptive interaction with an unstructured world.
- Robotic Locomotion and Manipulation: legged robots, robot arms, and hands that move and act reliably in complex terrain and contact-rich tasks.
- Biohybrid Robots: robots built from living cells, engineered tissue, and synthetic materials, actuated by muscle and powered by chemical energy.
- Perception and Computer Vision: 3D reconstruction, object recognition, and scene understanding that give robots reliable perception of their surroundings.
- Human-Robot Interaction: sensory-motor interaction between humans and machines for assistive, rehabilitative, and cooperative tasks.
- Computational Design and Fabrication: simulation, optimization, and learned surrogate models to design and fabricate efficient, bioinspired robots.
- Reinforcement Learning and Machine Learning: data-driven methods that let robots learn new skills and adapt to new tasks and environments.
- Humanoid Robotics and Tactile Sensing for Manipulation: humanoid loco-manipulation, whole-body control, and tactile sensing that let robots reason across touch and vision to handle objects dexterously.
- Motion Planning and Control: algorithms for navigation, control, and decision-making in dynamic environments.
- Safety-Critical Robotic Systems: robots that perform reliably under uncertainty, in particular when they work alongside humans.
You define your doctoral project together with your supervisor during your first months.
Profile
- A Master's degree in mechanical or electrical engineering, computer science, robotics, bioengineering, materials science, or a closely related field, completed by August 2027
- An excellent academic record in both your Bachelor's and Master's studies
- Demonstrated experience in one or more of the research areas above, ideally a project you carried from idea to a working result on real hardware
- Strong analytical and problem-solving skills, and the drive to do independent research
- Strong programming skills; experience with robotics software frameworks is a plus
- Excellent written and spoken English
Workplace
Workplace
We offer
- A fully funded doctoral position at ETH Zurich, employed at the ETH doctoral salary rate with full social benefits
- Supervision by a RobotX professor and access to the RobotX network of robotics groups across ETH Zurich
- Start date by agreement in 2027
- Your career with impact: Become part of ETH Zurich, which not only supports your professional development, but also actively contributes to positive change in society.
- We are actively committed to a sustainable and climate-neutral university.
- You can expect numerous benefits, such as public transport season tickets and car sharing, a wide range of sports offered by the ASVZ, childcare and attractive pension benefits.
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We value diversity and sustainability
In line with our values, ETH Zurich encourages an inclusive culture. We promote equality of opportunity, value diversity and nurture a working and learning environment in which the rights and dignity of all our staff and students are respected. Visit our Equal Opportunities and Diversity website to find out how we ensure a fair and open environment that allows everyone to grow and flourish. Sustainability is a core value for us – we are consistently working towards a climate-neutral future.
Requirements mentioned in the advert
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English: unclear
• Excellent written and spoken English
Workload: 100%
Workload excerpts
100%
Automatic text checks can miss context.