苏黎世联邦理工大学格罗宁根大学最新岗位制博士项目分享

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苏黎世联邦理工大学

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

ETH Zurich | Institute of Robotics and Intelligent Systems

截止时间: 招满即止

The Soft Robotics Lab within the Institute of Robotics and Intelligent Systems at ETH Zurich is inviting applications for several 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 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.

We do not hire against a narrow project description. Your thesis topic is something we shape together in your first months. Tell us which of our directions pulls at you, and what you would want to build.

Project background

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 (Nature Communications, 2024). Our low-voltage HASEL actuators run near 1100 V, are safe to touch, and work untethered and underwater (Science Advances, 2024). We recently extended these muscles to full antagonistic motion ranges (ICRA 2025) and to a sensorless, inherently compliant anthropomorphic hand driven entirely by electrohydraulic actuation (IROS 2026).

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 (Science Advances, 2025), embedded sensors directly into muscle for closed-loop control of proprioceptive biohybrid robots (Advanced Intelligent Systems, 2025), and established functional volumetric bioprinting with xolography (Advanced Materials, 2026). Co-optimized volumetric muscle designs for large dynamic deformations are in press at Nature Communications (Balciunaite et al., 2026). The same fabrication line reaches clinical work: with University Hospital Zurich we printed implantable reinforced cardiac tissue patches (Advanced Materials, 2025).

Dexterous manipulation and robot 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 (IROS 2025). On that hardware we work on imitation learning and diffusion policies, cross-embodiment skill transfer through latent action diffusion (ICRA 2026), sample-efficient reinforcement learning and policy fine-tuning directly on the real robot, vision-language-action models for contact-rich tasks, and tactile representation learning on our high-resolution sensorized skin (ICRA 2024). We also build controllable dexterous world models for training and evaluation, and a benchmark of dexterity for anthropomorphic hands. Whichever side you come from, the offer is the same: the hand, the skin, the simulator, and the people who designed all three sit in one room. Build a mechanism here and someone will have a policy running on it within weeks. Build a policy here and you can change the mechanism when the mechanism is what is wrong.

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 (Nature, 2023). We close the sim-to-real gap with learned residual physics (RA-L, 2024, Best Paper Award), and we released SORS, a modular high-fidelity soft-robot simulator, at RoboSoft 2026.

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 (CoRL 2024).

Job description

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 supervise semester and Master's projects, which is how most of our doctoral students learn to lead work, and you will collaborate day to day across our hardware, muscles, and machine learning teams
You will complete a doctorate at ETH Zurich alongside the research, including the coursework of the D-MAVT doctoral programme and a share of teaching in one of our courses

Profile

You are curious, highly motivated, and independent, and you want to make a real difference with your research
You work best in a team. You are respectful, and you thrive when you can collaborate with others and support them

Through your prior experience, you have ideally already demonstrated:

A completed or nearly completed Master's degree in mechanical engineering, robotics, mechatronics, electrical engineering, computer science, materials science, bioengineering, or a closely related field
Depth in at least one of: hands-on system building and mechatronics (CAD, FEA, 3D printing, machining, molding, electronics, motor control, robot integration), machine learning and control for real robots, soft or bio-inspired materials and actuators, tissue engineering and biofabrication, or physics-based simulation
Evidence that you carry work through to reality. In a thesis, a semester project, a competition team, or an internship, you have taken something from first idea to a result that worked on real hardware, not only to a simulation benchmark
Substantial project or thesis work we can read, and ideally a publication or preprint, though we do not expect one at this stage
Strong written and spoken English, and comfort explaining your work clearly
Strong motivation for interdisciplinary, experimental research and the curiosity to develop new skills throughout the doctorate
A collaborative, supportive mindset and the drive to make a real difference with your research
A clear idea of what you would want to work on with us, and why it matters

格罗宁根大学

PhD position Neuroscience

University of Groningen | Faculty of Science and Engineering

截止时间：18 September 2026

Understanding how patterns of neural activity give rise to behavior is a central challenge in neuroscience. Most of what we know about this relationship comes from rodent experiments performed under tightly controlled laboratory conditions. While these approaches are essential for identifying neural mechanisms, they capture only a fraction of the behavioral repertoire animals display in more complex environments.

What are you going to do?

In this project, you will investigate how neural population activity relates to behavior across environments ranging from standardized laboratory assays to large outdoor enclosures. Using miniaturized calcium imaging, you will record the activity of large populations of neurons in freely behaving mice and determine how neural activity relates to moment-to-moment behavioral changes.

A major component of the project will make use of large outdoor mouse enclosures at the University of Groningen. These environments allow mice to express a rich repertoire of species-typical behaviors, including exploration, shelter use, social interactions and responses to changing environmental conditions. You will combine RFID tracking, multi-camera recordings and deep-learning-based behavioral analysis to identify reproducible behavioral states and understand how they vary across individuals, sexes and environmental contexts.

Pharmacological manipulations will be used to experimentally validate specific behavioral states and investigate how they are modulated by neural systems involved in anxiety and behavioral adaptation. You will subsequently combine wireless miniature calcium imaging with automated behavioral monitoring to uncover the neural dynamics associated with these behaviors.

Methods: miniature calcium imaging, deep-learning-based behavioral tracking, RFID tracking, computational analysis of neural population activity, stereotaxic surgery, pharmacological manipulations and histology.

Who are you?

Candidates who do not meet all formal criteria but demonstrate strong affinity and motivation for the topic are strongly encouraged to apply

Ideally, you have:

A Master’s degree in neuroscience, biology, biomedical sciences or a related discipline, with relevant experience in behavioral, computational and/or systems neuroscience. If you have completed all the requirements of your degree but are awaiting the official award, a statement from your university that all requirements are met is sufficient.
A strong interest in neural circuits and rodent behavior.
Experience with animal experimentation. Preference will be given to candidates with an Article 9 license (FELASA accreditation), or previous hands-on experience with animal experimentation.
An interest in combining behavioral neuroscience with quantitative and computational approaches. Preference will be given to candidates that have previous experience analyzing neural or behavioral datasets, or used deep-learning based behavioral tracking (for example DeepLabCut or SLEAP).
Experience with, or a strong motivation to learn Python or Matlab.
An excellent command of English (oral and written). Candidates are exempted from proving proficiency in English if they (i) completed a secondary education (HAVO or VWO certificate) in the Netherlands, (ii) are a native English speaker, or (iii) completed a Bachelor or Master degree programme which was fully taught in English. If you are not exempt please provide sufficient evidence with your application.

What can you expect from us?

In accordance with the collective labor agreement for Dutch universities, we offer a salary of at least € 3.204 up to a maximum of € 4.051 (promovendus) gross per month for a full-time employment contract.
232 vacation hours per year, based on a 38-hour workweek (1.0 FTE). You can also work more or fewer hours in exchange for more or fewer free hours. For example, with a 40-hour workweek, you save 96 extra free hours, and with a 36-hour workweek, you lose 96 hours.
End-of-year bonus of 8.3% and 8% holiday allowance.
Extensive opportunities for personal and professional development.
A full-time position for 48 months (4 years). The successful candidate will first be offered a temporary position of one year with the option of renewal for another 3 years. Prolongation of the contract is contingent on sufficient progress in the first year to indicate that a successful completion of the PhD thesis within the next 3 years is to be expected. A PhD training program is part of the agreement, and the successful candidate will be enrolled in the Graduate School of Science and Engineering at the University of Groningen.

Interested?

Does this vacancy appeal to you? If so, click on the button below and apply straightaway.

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