Postdoctoral Positions in Robot Learning and Soft, Musculoskeletal, and Biohybrid Robotics

Depending on your direction, your work will emphasize different parts of the following. All of it happens in a lab where hardware, biology, and learning sit in the same room. You will take a research idea from concept to a working system: designing the architecture, building it, integrating sensing and control, and validating it through systematic real-world experiments. If your focus is systems design, you will design and build the robots themselves: mechanisms and compliant structures, actuators and tendon routing, embedded electronics and motor control, and the sensor integration that makes a machine measurable. You will own a system from CAD through fabrication to hardware that still runs six months later. If your focus is learning, you will develop policies and perception that run on real, compliant, contact-rich hardware: imitation learning, real-world reinforcement learning and fine-tuning, sim-to-real transfer, and multimodal representations that use touch as well as vision. You will help define the benchmarks that make such claims measurable. Each design cycle feeds the next, so rapid prototyping, measurement, and iteration sit at the heart of every project. Drawing inspiration from biological musculoskeletal systems, you will engineer how bones, joints, tendons, and muscles can be recreated with compliant materials, artificial actuators, or living tissue, and how their interplay produces strength, dexterity, and robustness. You will build robots that derive much of their capability from their embodiment, achieving rich, adaptive behavior with less reliance on complex centralized control. If your focus is biohybrid systems, you will work in our biological laboratories at ETH, culturing and bioprinting tissue and turning it into a controllable actuator. You will publish at the top venues in the field, release open-source hardware and code where it helps the community, and present your work internationally. You will co-supervise doctoral and Master's students, help shape the direction of your subgroup, and collaborate day to day across our hardware, muscles, and machine learning teams. You will build your own research line here, and we will support you in funding it, whether through SNSF Ambizione or Postdoc.Mobility, an ERC Starting Grant, or a Marie Skłodowska-Curie fellowship.

The Soft Robotics Lab within the Institute of Robotics and Intelligent Systems at ETH Zurich is inviting applications for several open postdoctoral positions. Our lab's goal is to build, model, and control robots in a fundamentally different way, so that they become more flexible, dexterous, capable, and adapt better to their environment. We work along four directions: soft and musculoskeletal robotics, biohybrid living systems, dexterous manipulation and robot learning, and simulation for embodied AI. We are looking for exceptional candidates in any of them. This round we especially want two profiles: people who design and build the robots, and people who make policies run on them.

• A completed PhD in mechanical engineering, robotics, mechatronics, electrical engineering, computer science, materials science, bioengineering, or a closely related field

• Deep expertise in at least one relevant area: hands-on system building and mechatronics (CAD, FEA, 3D printing, machining, molding, electronics, motor control, robot integration), machine learning and control for physical robots, soft or bio-inspired materials and actuators, tissue engineering and biofabrication, or physics-based simulation

• Evidence that you carry work through to reality. You have taken a system or a method from first idea to a validated result on real hardware, not only to a simulation benchmark, and you are willing to get into the loop of building and debugging the robot your methods run on

• A record of peer-reviewed publications in leading venues that demonstrate both technical depth and real-world impact

• Prior experience mentoring or co-supervising Master's or PhD students, and a collaborative, supportive mindset

• Strong written and spoken English, and comfort communicating your work to both academic and non-specialist audiences

• A genuine appetite for interdisciplinary, experimental research and the curiosity to develop new skills across traditional disciplinary boundaries

• A clear sense of what you would want to work on with us, and why it matters