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acquisition and processing techniques to study the Earth’s shallow subsurface. Project background Switzerland has committed to achieving net-zero greenhouse gas emissions by 2050. CCS technologies are a key
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language. We offer Opportunities to collaborate with international research groups, enabling you to build a strong scientific network. The possibility to mentor students and interns and contribute
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Group in the Social Networks Lab at ETH Zürich is developing network data science methods and applying them in a variety of domains. Our current research focus is on sports analytics and we seek to expand
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(i) identify their composition and distribution among species, (ii) examine genomes for positive selection to detect sterol-related innovations and associated genes, and (iii) assess sterol functions
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on musculoskeletal biomechanics and mechanobiology across all scales. Project background This project is part of the EU-funded Print4Life , a Marie Sklodowska-Curie (MSCA) doctoral network led by Prof
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expertise will extend to various areas, including quantum Monte Carlo, machine learning, quantum computing, quantum machine learning, and tensor networks. These and other techniques will allow us to confront
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agentic embedded AI: Networks of autonomous micro-agents for cooperative sensing and learning. Job description Conduct experimental and theoretical research along the project’s core directions. Implement
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. Our technological focus is thermal energy systems, sustainable carbon feedstock, and CO2 capture, utilization, and storage. Project background To achieve Switzerland’s net-zero climate target by 2050
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network of collaborators. Position Details: Institution: ETH Zurich, Department of Management, Technology, and Economics (D-MTEC) Chair: Strategic Management and Innovation (Prof. Dr. Georg von Krogh) Start
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opportunities with leading experts in chemical analytics of trace elements, modeling, biogeochemical cycles, and atmospheric processes. Support programmes and networking opportunities such as attending