Open Positions

PhD Position in Robotic System Integration for Musculoskeletal Robotic Hands

Join out team for a fully-funded PhD position in Robotic System Integration for Musculoskeletal Robotic Hands.

The doctoral research will be multidisciplinary, involving the analysis of current musculoskeletal technologies and the design of innovative robotic hands.

You will focus on:

- Analyzing existing muscle technologies and robotic hand systems, studying natural mechanisms of manipulation
- Designing and developing a robotic hand using muscle-like actuators and tendons, aiming for superior performance compared to traditional motor-driven hands
- Integrating sensing and proprioceptive technologies to enhance the hand's functionality and control
- Employing advanced control strategies and machine learning approaches, including imitation learning, for effective manipulation
You will closely collaborate with other PhD students working on muscle technology, manipulation, control, and machine learning.

The output of the PhD thesis will significantly contribute to the advancement of musculoskeletal robotics, particularly in the field of manipulation, setting a new benchmark for robotic hands.

We are seeking a highly motivated, exceptional candidate with a passion for pioneering research in robotic system integration and musculoskeletal robotics.

The ideal candidate should:

- Hold a master's degree in robotics or a related field such as mechanical engineering or electrical engineering
- Have an excellent track record and meet the general admission requirements for a doctorate at ETH Zurich
- Possess prior research experience in robotics, actuator development, or related areas
- Be experienced or have a keen interest in machine learning, control theory, and sensing technologies
- Demonstrate the ability to work collaboratively in an interdisciplinary team
- Experience in design and fabrication of robotic systems, especially those incorporating novel actuator technologies, is highly desirable
Familiarity with machine learning techniques, such as imitation learning, and a background in biological or biomimetic systems would be advantageous.

Apply: Details and application are here

PhD position in Electrohydraulic Actuators for Robotic Systems

Project background
Electrohydraulic actuators are a novel technology that has demonstrated application potential thanks to their smart topology design and capacitive self-sensing capability, which ease control and integration into mobile robots. However, many challenges remain, such as the actuators' low stroke, low reliability, slow and inconsistent production, and bulky high voltage Power supply requirements. Your work aims to find creative and effective solutions to these challenges and potentially conceive completley new muscle-like actuator technologies.

Job description
The doctoral studies will focus on the co-optimization of the structure and control of low voltage electrohydraulic actuators, which is an integrated process that starts from material selection and design choice suitable for mass fabrication and ends with the proper control policies. Materials dictate the fundamental physics within the actuators, and design determines actuation principles, which are crucial in efficiency, force, and speed improvements. Accurate and consistent fabrication of soft actuators is a must for future product developments. The ability to accurately control the actuators is key to a wide range of applications and can be acquired with help from the self-sensing capability of the actuators. The actuators will also be integrated into robotic systems as functional demonstrators that can operate in real-world environments.

The doctoral thesis work will focus on:
-The actuator materials selection and design optimization
-Their characterization and the implementation of self-sensing capability
-The integration of actuators into robotic systems
-Scalable fabrication techniques including quality control of the actuators

The output of the Ph.D. thesis will be highly relevant as a competitive soft actuator element for building the next generation of soft and musculoskeletal robots.

Your profile
We are looking for a highly motivated, outstanding individual who is curious to continuously consider perspectives of different fields and work in an interdisciplinary environment. We particularly value diligence, perseverance, and curiosity in your day-to-day scientific work.
You should:
-Hold a master's degree in an engineering field relevant to electrohydraulic actuators or soft robotics, such as mechanical engineering, electrical engineering, or materials science
-Have an excellent track record and meet the general admission requirements for a doctorate at ETH Zurich.
-Have previous research experience in engineering-related topics
-Have previous experience working with actuators and robotic systems
-Have had exposure to thin film fabrication techniques and potentially be familiar with functional polymers
-Have experience in developing actuators, sensors, or other functional structures

Apply: Details and application are here.

PhD position in Differentiable Simulation and Machine Learning for Musculoskeletal Robotics

Join our team for a fully-funded PhD position focusing on design optimization of electrohydraulic musculoskeletal robots using differentiable simulation and machine learning.

Role:

• Concentrate on simulation and computational design with machine learning surrogates.
• Develop new simulation frameworks and validate physically against real-world robotic systems.
• Present findings at international conferences.
• Supervise students, assist in teaching, and draft grant proposals.

Candidate:

• Passion for robot optimization and exploring diverse research fields.
• Background in numerical simulations, robotics, and computational modeling.
• Computer science or engineering degrees with an excellent academic record.

Apply: Details and application are here.

PhD position in Machine Learning for Mesh-based Representations of Deformable Objects

Join the Soft Robotics Lab for a doctoral role focused on real-time mesh-based reconstruction of deformable objects and robots from point clouds. This collaboration with the Swiss Data Science Center (SDSC) and the Computational Robotics Lab aims to create an efficient tool for real-time scene generation and object manipulation.

Role:

• Work on physics-based object simulation and point cloud to mesh reconstruction.
• Validate simulations with real-world robotic systems and objects.
• Develop and publish software frameworks.
• Present findings at global conferences.
• Supervise students, assist in teaching, and draft grant proposals.

Candidate:

• Passionate about robot computer vision for manipulation.
• Curious about new technologies and complex objects.
• Resilient in the face of challenges.
• Background in object representations, computer graphics/vision, and physics-based simulation.
• Experience with robotics learning, simulations, and deformable object manipulation.
• Computer science or engineering degrees with an excellent academic record.

Apply: Details and the application can be found here.

PhD position in Differentiable Simulation and Machine Learning for Musculoskeletal Robotics

Job Description
At the Soft Robotics Laboratory, we offer a fully-funded doctoral position for computational design optimization of electrohydraulic musculoskeletal robots. Our research group creates artificial muscles and attaches them to a rigid skeleton with ligaments and tendons to create adaptable, complex robotic systems. To achieve design optimization, we first need a physically validated simulation of robots driven by new electrostatic/electrohydraulic artificial muscles. We then apply this simulation in optimization settings for, e.g., both shape and control, in a multi-variable multi-objective co-optimization setting. We therefore consider implementing differentiable solvers for this application, starting from first-principles, and later developing a deep learning surrogate for faster, potentially real-time, computation.
This doctoral position will focus mainly on the simulation and computational aspects, while most hardware components are fabricated and built by colleagues in the Soft Robotics Laboratory. Simulation to reality validation needs to be performed through experimental setups that the candidate should be able to design and use. A strong interest in working hands-on with robotic systems and validating simulations in the real world on robots is desirable.
As a PhD student, you will develop and publish on new software frameworks and their physical validation. You will regularly present your work at international robotics and machine learning conferences. Your responsibilities will also include supervising bachelor and master students in their thesis works, supporting the Soft Robotics Laboratory in teaching of its graduate classes, and in preparing grant proposals.

Your profile
You are interested in the optimization of robots for specific functional requirements, and motivated to independently explore various fields of research for combining their knowledge to achieve this goal. You are curious about novel technologies, and learning about new muscle actuator types and understanding their inner workings. You persevere through challenges faced throughout the project, and are able to quickly adapt when experiments do not deliver the desired results. You are a diligent worker that is driven to publish new insights and lead the research community forward by communicating your findings to both a smaller community of researchers, as well as to a broader public audience.
You have background knowledge in numerical simulations, computational modeling, and shape optimization. Ideally you have previously worked with robotics and (differentiable) simulations, with hands-on experience testing robots for their performance, and matching with simulated results. Machine learning knowledge, especially in the field of deep learning for scientific computing, can be beneficial. Proficient communication skills in English are required.
You should have a computer science or engineering background, with BSc and MSc degrees, in computer science, mechanical or electrical engineering, computational engineering, applied physics, or a related field. Your academic record is outstanding.
ETH Zurich is a family-friendly employer with excellent working conditions. You can look forward to an exciting working environment, cultural diversity, and attractive offers and benefits.

We look forward to receiving your application. Please submit the following application documents using only the ETH online portal in a single merged PDF document, titled with your last name and initials as well as the application date (for example, 20230601_DoeJane_application) in the following order:
- Cover letter with a description of your research achievements and research interests
- Detailed CV
- Transcripts of all degrees (English)
- Names and contact information of at least three references
- Representative published research work (Papers, thesis if possible).

Further details and the application can be found here

Funded Postdoctoral Fellowship Options

• AI Center Postdoc Fellowship
• ETH Postdoc Fellowship
• SNSF Postdoc Fellowship
• external pageBranco Weiss Fellowshipcall_made
• external pageSNSF Ambizione Grantcall_made