A new PhD position in mechanical engineering is available at ETH Zurich. Applications will be evaluated immediately.
You develop computationally efficient physics models that capture only the relevant degrees of freedom of a soft robot as defined by their tasks. In your research, you will learn to describe non-linear deformations of hyperelastic materials in real-time. You pursue dual research tracks to achieve a universal soft robotic modeling framework: For symmetrically-shaped robots, you develop minimal parameter methods sufficient enough to capture the dynamics and impedance of the deformable structures while being computationally efficient. For robots of irregular shape, you develop large scale finite element methods and make those models tractable by expanding on techniques such as model order reduction with state observers and deep learning methods. You advance the state of the art of the current modeling approaches used in the dynamic closed-loop control of soft continuum robots. You continuously design, simulate, and test your modeling algorithms on your deformable robots so that they become more able to dexterously interact with an inherently deformable world. Your system modeling and model-based control approaches will be design-agnostic and user-friendly to facilitate broad adoption in the robotics (new robotics scholarship positions) community. You will conceive and create an open-source modeling framework for soft robots. The development of such a framework will be accelerated through active collaborations with other researchers working on numerical simulations of physical systems such as SOFA and on toolboxes for dynamical systems modeling such as Drake.
You are extremely curious, very driven, highly independent, and you want to make a real difference with your research. Through your prior experiences, you have shown your understanding in: Designing, and testing modeling algorithms for robots or deforming systems Creating simulations of deforming systems for testing out new ideas Realizing on-system testing to show your modeling results on real-world devices or natural systems A good understanding of physical modeling and machine learning methods is essential for the successful completion of the proposed research project. It would be greatly advantageous if you are already proficient in C++ and Python. You will be able to collaborate with other research labs, and you will have access to support from R&D experts, scientists, engineers, and doctoral students with background in mechanical engineering, electrical engineering and computer science.
ETH Zurich is one of the world’s leading universities specialising in science and technology. We are renowned for our excellent education, cutting-edge fundamental research and direct transfer of new knowledge into society. Over 30,000 people from more than 120 countries find our university to be a place that promotes independent thinking and an environment that inspires excellence. Located in the heart of Europe, yet forging connections all over the world, we work together to develop solutions for the global challenges of today and tomorrow.
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