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on infectious disease dynamics using a broad range of mathematical, computational, and experimental approaches to study the population dynamics and evolution of infectious pathogens on both the within
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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
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100%, Basel, fixed-term ETH Zurich is a world-leading university dedicated to advancing science, engineering, and technology. The position is embedded in the Computational Biology (CoBi) group
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; collaborating closely with molecular biologists, computational modelers, and clinical and preclinical research partners; documenting results clearly and contributing to publications and presentations; and
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networks Additional responsibilities include: Publishing in top-tier scientific journals and presenting at leading conferences Assisting with BSc/MSc supervision and research proposals Teaching within
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, electrical engineering and computer science to design highly efficient and sensitive imaging and inference approaches to help guide diagnosis and treatment in cardiovascular patients. Project background Our
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the Alps supercomputer at the Swiss National Supercomputing Centre (CSCS), which features over 10,000 NVIDIA Grace Hopper GPUs, making it one of the most powerful AI-focused computing resources in
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to disseminate findings Profile Qualification PhD in mechanical engineering, biomedical engineering, materials science or closely related field Experience in microneedle fabrication (e.g., by 3D printing
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Hangartner ariane.hangartner(at)usys.ethz.ch (for administrative questions). About ETH Zürich ETH Zurich is one of the world’s leading universities specialising in science and technology. We are renowned
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Materials science and technology are our passion. With our cutting-edge research, Empa's around 1,100 employees make essential contributions to the well-being of society for a future worth living