127 parallel-and-distributed-computing-"DIFFER" positions at ETH Zurich in Switzerland
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100%, Basel, fixed-term ETH Zurich is a world-leading university dedicated to advancing science and technology. The advertised position is based in the Computational Biology (CoBi) group led by Prof
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100%, Basel, fixed-term ETH Zurich is a world-leading university dedicated to advancing science and technology. The advertised position is based in the Computational Biology (CoBi) group led by Prof
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of experience in a similar role, preferably in a university environment You are responsible and work independently, systematically and accurately You enjoy contact with different stakeholders and put their needs
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science journey, from the collection and management of data to machine learning, AI, and industrialization. The Center comprises a multi-disciplinary team of data and computer scientists and experts in
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develop and apply computational approaches to identify policy strategies that are politically feasible and compatible with changing land-use demands, while also considering the distributional impacts
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broader research agenda focused on how digital infrastructure and computational tools can support (or hinder) progress toward effective, coordinated, and equitable biodiversity governance. Research topics
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. Sabine Rumpf), and the Flore-Alpe Alpine Botanical Garden (Prof. Christophe Randin). Climate change is shifting the spatial distribution of suitable habitat for all species, but the vast majority
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100%, Zurich, fixed-term The Distributed Computing (DISCO) Group is a research group at ETH Zurich, led by Prof. Dr. Roger Wattenhofer . We are interested in a variety of research topics on new and
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synchronize different physiological recordings including EEG, ECG, respiratory recordings and pupillometry. The successful candidate will be part of all aspects of scientific work making this an exciting and
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therapeutic agents to reach the brain with unprecedented precision. By enabling targeted drug delivery, our approach could dramatically improve therapeutic outcomes while minimizing side effects. Unlike