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and production enabled through digital manufacturing techniques. To our infrastructure belongs the Robotic Fabrication Laboratory (RFL), a unique digital construction environment, which allows for world
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of semiconductor devices. The aim is to predict these properties for arbitrarily large structures, at a DFT-level of accuracy. As a starting point, you will extend the large-scale equivariant GNNs we develop
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Ph.D. Position in Organic Chemistry, Polymer Chemistry, and/or Sol–Gel Chemistry & Materials Science
energy-related applications. Our research portfolio spans fundamental materials chemistry, process–structure–property relationships, and application-driven R&D, in close collaboration with academic and
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is to build efficient and robust computational tools for analyzing complex engineering systems. Applications include structural dynamics and other dynamical systems relevant to real-world engineering
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opportunity to work with leading experts across Europe to design and deliver sustainable meta-materials for vibration mitigation, self-aware meta-components and carbon-efficient meta-structures
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are asked to negotiate rules and anticipate the impacts of innovations that can barely be tracked, often with limited resources and no structured access to expertise. Scientists, meanwhile, lack clear entry
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. Through cross-institutional collaboration and industry engagement, COMBINE provides structured doctoral training, secondments, and interdisciplinary research experiences. PhD position COMBINE-DC17 is hosted
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80%-100%, Zurich, fixed-term We are looking for a Research Engineer to join ongoing and future research projects at the intersection of machine learning, and structural design (e.g. trusses, space
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100%, Zurich, fixed-term The Laboratory of Energy Science and Engineering (LESE, ETH Zürich) invites applications for a PhD position in the field of CO2 capture, with a focus on structure
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models, and unsupervised learning to identify high-order structure in neural and molecular data. • Conduct statistical modeling of temporal trajectories and population dynamics across thousands of neurons