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data, and interpret results Prepare and present research findings at scientific conferences and in peer-reviewed journals Collaborate with other team members and contribute to the overall research goals
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to staff position within a Research Infrastructure? No Offer Description PhD Position in Physics-Informed Machine Learning for Cardiac Magnetic Resonance The CMR Zurich group at the Institute
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kinetics, coarse-graining across time and length scales, machine learning from small and multi-fidelity datasets, and autonomous discovery workflows. You will collaborate with experimentalists at ETH Zurich
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Zurich translates the science of materials processing into societally impactful technologies through student entrepreneurship and interdisciplinary collaboration. For this research project in partnership
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engineering and digital design: Enabling high-performance timber plate structures through simplified connections and planning processes”. The project is a collaboration between Gramazio Kohler Research (Chair
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carbohydrates, namely the core-1-derived O-glycans, shape the lymphatic endothelial cell glycocalyx and its recognition by myeloid immune cells. Job description The successful candidate will: Learn to work with
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of applying molecular models at process scales, the project combines efficient mathematical concepts like automatic differentiation with backpropagation – the same concept that powers machine learning and
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interest in translational health technologies Excellent command of written and spoken English Good communication skills and capacity for interdisciplinary collaboration Ideally: Experience in sensor design
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collaboration with clinicians and interdisciplinary research, we aim to translate innovative concepts into clinically relevant systems that expand access to high-quality medical care, while also exploring new
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surveys Processing and interpreting time-lapse seismic data to track the migration and evolution of the CO₂ plume Collaborating within an interdisciplinary team of geophysicists and reservoir engineers