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

Doctoral Position in Soft and Musculoskeletal Robotics, Biohybrid Systems, and Robot Learning 100%, Zurich, fixed-term

The Soft Robotics Lab within the Institute of Robotics and Intelligent Systems at ETH Zurich is inviting applications for open doctoral 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 learning, and simulation for embodied AI.

We are looking for exceptional researchers in any of them.

We do not hire against a narrow project description. We hire people who will define their own. Tell us which of our directions you want to push, and why you are the person to push it.

Today's robots are mostly rigid, fragile, and a world apart from the agility and resilience of biological bodies. Our bet is that the next generation of robots will be soft, musculoskeletal, and in part alive. They will be built to make contact with the real world rather than to avoid it. We pursue this across four directions, and a strong candidate will find a home in one of them and borrow from the others.

Soft and musculoskeletal robotics. We build bodies from compliant structures, bones, joints, and tendon-like actuation. Our electrohydraulic musculoskeletal leg jumps, moves fast, and adapts to terrain at roughly 1.2% of the energy a motor-driven leg needs. Our low-voltage HASEL actuators run near 1100 V, are safe to touch, and work untethered and underwater. We recently extended these muscles to full antagonistic motion ranges and to a sensorless, inherently compliant anthropomorphic hand driven entirely by electrohydraulic actuation.

Biohybrid living systems. We grow engineered muscle and use it to actuate machines. We bioprinted multicellular muscle-tendon units that transmit force along a real musculoskeletal path, embedded sensors directly into muscle for closed-loop control of proprioceptive biohybrid robots, and established functional volumetric bioprinting with xolography. Co-optimized volumetric muscle designs for large dynamic deformations are in press at Nature Communications. The same fabrication line reaches clinical work: with University Hospital Zurich we printed implantable reinforced cardiac tissue patches.

Dexterous manipulation and learning. We build hands and the policies that run them. One of our initial hand designs is now commercialized through our spin-off Mimic Robotics. ORCA is our open-source, reliable, and cost-effective anthropomorphic hand for uninterrupted dexterous task learning. On top of that hardware we work on cross-embodiment skill transfer through latent action diffusion and on sample-efficient policy fine-tuning directly on the real robot.

We also build controllable dexterous world models, high-resolution sensorized skin, and a benchmark of dexterity for anthropomorphic hands.

Simulation, fabrication, and embodied AI. Building these robots requires tools that did not exist. Vision-Controlled Jetting prints rigid skeletons, soft tissue, tendons, and sensors in one pass, including a full musculoskeletal hand and forearm. We close the sim-to-real gap with learned residual physics, and we released SORS, a modular high-fidelity soft-robot simulator, at Robo Soft.

Underwater and aerial systems run through all of this, from SoFi and tendon-driven swimmer digital twins to our open-source soft aerial manipulation platform.

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
• 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 learning, you will develop control and perception methods that work on real, compliant, contact-rich hardware, not only in simulation, and you will help define the benchmarks that make such claims measurable
• 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…