221 computer-science-intern-"https:"-"https:"-"https:"-"https:"-"CUBO" positions at ETH Zurich in Switzerland
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collaboration with various stakeholders (engineering companies, Swiss Armed Forces, armasuisse, international collaborators) to ensure efficient roll-out of the system Profile MSc degree in Geophysics, Seismology
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The current era of artificial intelligence is predominantly driven by advances in computational power and infrastructure. As models scale to unprecedented sizes, their capabilities are enhanced
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development. Job description We are searching for a scientific assistant who assists and coordinates teaching activities in the international master program Spatial Development and Infrastructure Systems
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, Computer Science, Applied Mathematics, or a field focused on the intersection of Machine Learning and Optimization Proven expertise in surrogate modelling, specifically in designing neural architectures
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Participation in international collaborations within a major European project Supervision and Environment The postdoctoral researcher will be hosted at the Chair of Engineering Geology at ETH Zurich and
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of emerging technologies balanced against their dark sides. Our research at the intersection of data, behavioural, and computer science draws on data from real-world and experimental settings The Centre for AI
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convective heat transfer with the surrounding air. Within our research group at ETH Zurich, we are developing computational workflows for predicting temperature fields in machine tools using computational
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within the ETH environment and in national and international RDM networks. Profile PhD in natural sciences, engineering, computer science, or comparable fields Several years of experience in research data
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of Medical Microbiology at the University of Zurich, the Department of Informatics at ETHZ and several further partners, we address the challenge by the combining microfluidic technology, sequencing and fast
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at the University of Zurich, the Department of Informatics at ETHZ and several further partners, we address the challenge by the combining microfluidic technology, sequencing and fast data analysis. In