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-based venture developed at the Structural Xploration Lab, building the Reuse Viability Index (RVI), an AI system that predicts the reuse value of building components before demolition, using data from
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looking for student research assistants with a background in computer science, data science, or related fields to support interdisciplinary research projects at the intersection of data science, artificial
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higher information content, and to apply them to challenging systems from inorganic chemistry and catalysis, as well as to organic radicals. Our group is also developing a new method based on optical
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databases. Interventions are therefore often planned using disjointed evidence and conservative heuristics, even where substantial data exist. The project Predictive, Resilient, Integrated Systems
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of Computer and Communication Sciences and the School of Life Sciences, as well as the EPFL AI Center. As part of an industry collaboration with Novartis, the lab is opening a postdoctoral position on
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background Organogenesis, the formation of organs during embryonic development, depends on tightly coordinated cell signalling, growth and mechanics. Our group combines quantitative imaging data with
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glaciers and their likelihood to be the source of large ice avalanches. The overarching goal of the project is to provide a data-driven method to create an index of hazard potential for all hanging glaciers
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of Information analysis, and intervention program optimisation. This position is part of an interdisciplinary SNSF project in collaboration with the Free University of Bozen-Bolzano, the Hagerbach Test Gallery
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10%-30%, Zurich, fixed-term As part of Grid2050 and NCCR Automation, we are building a high-performance, secure, and fault-tolerant data infrastructure to power cutting-edge energy research
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representations learned from retinal images, develop longitudinal models of disease progression, and build data-driven approaches for patient stratification and clinically relevant outcome prediction. The position