PhD in AI-Assisted Generative Design and Optimization of Compliant Mechanisms (F/M/D) 100%

Facing the challenges of our time - Help us grow and be more impactful! Your mission Help create engineering tools that combine mechanics, computation and AI to make the design of complex optomechatronic systems faster, more rigorous and more reusable. CSEM and the Engineering Design and Computing Laboratory of ETH Zurich are seeking a doctoral researcher to investigate how AI and advanced computational methods can support the design of high-performance optomechatronic systems. The research will be anchored in compliant mechanisms, where performance emerges from tightly coupled geometry, material behaviour, actuation, sensing, manufacturing and verification constraints. The ambition is not to treat AI as a black box. You will develop scientifically grounded methods that combine physics-based models, simulation data and engineering knowledge, and make their predictions traceable, testable and useful to engineers. Research focus The project will build on the outcomes of Guilain Lang’s doctoral thesis, “CAM2S2: Compliant AM Mechanisms Systematic Synthesizer” [link to the online thesis], which established a systematic framework for translating requirements into compliant mechanism designs. The new research will critically assess and selectively reuse, adapt or extend the methods and tools developed in CAM2S2, without being constrained to retain the complete existing framework. From this foundation, it will develop and validate AI-assisted methods to derive engineering insight from requirements, explore broader solution spaces and generate reusable models for mechanism and optomechatronic system design. The exact thesis plan will be refined with the selected candidate and the supervisors. Expected research directions include: