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methods and systems to overcome the limitations of today’s materials processing technologies. One particular area of interest is the design and fabrication of active structures through hybrid production
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focused on the intersection of Machine Learning and Optimization Proven expertise in surrogate modelling, specifically in designing neural architectures for emulating constrained optimization problems
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integrates state-of-the-art synthetic biology with advanced nanotechnology, and electrogenetic interfaces to engineer human cells for next generation bioelectronic medicine, designing programmable cells
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chemical structures that interface with and actuate cellular activities, we design programmable cellular implants and devices for therapeutic applications. By integrating fundamental discoveries with
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the Job related to staff position within a Research Infrastructure? No Offer Description Postdoc in Machine Learned Semiconductor Material Properties for Quantum Transport Simulations The simulation
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enable new routes toward fault-tolerant quantum computation and open exciting opportunities for exploring frontier problems in quantum information dynamics. The successful candidate will: Design, build
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, robust acquisition strategies. Design, execute, and document high-quality measurements for internal projects and external collaborations, including appropriate QC, troubleshooting, and clear reporting
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to the development, adaptation, and application of machine‑learning models tailored to RODI data (in collaboration with project partners). Designing and implementing an innovative image‑based database to manage and
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politicization affect technology adoption, industrial development, policy design, and its socio-technical and political feedback effects. The project is embedded within ETH Zurich’s new Einstein School of Public