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will work within the Computational Mechanics Group of ETH Zürich in collaboration with industrial partners. You will have the unique opportunity to learn, develop and apply a range of cutting-edge
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strong willingness to learn A solid foundation in experimental research, data analysis, and scientific methods Interest in machine learning and data-driven approaches to materials discovery Strong interest
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and original surveys with causal inference and machine learning methods to bring new evidence to bear on the urgent problems policymakers and practitioners face. We collaborate with a nonprofit
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degree in Computer Science, Data Science, or a related technical field with strong foundations in machine learning OR Master's degree in Mathematics, Statistics, Physics, or other quantitative discipline
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partners. You will have the unique opportunity to learn, develop and apply a range of cutting-edge modeling and computational techniques. You will also be exposed to experimental methods used to produce data
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committed to a sustainable and climate-neutral university . You can expect numerous benefits , such as public transport season tickets and car sharing, a wide range of sports offered by the ASVZ , childcare
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with machine learning, clustering methods or generative AI (preferred but not required) Willingness and ability to collaborate with researchers from different backgrounds, stakeholders and the general
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of the CDL group and the postdocs, on closed-loop control systems with machine learning, and design for fabrication workflows. In addition to conducting their research, Ph.D. students at ITA get the
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spectroscopy, along with cutting-edge machine learning approaches and statistical analysis, to enable timely identification of high risk for the chronic wound formation. Your profile We are looking for a highly
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committed to a sustainable and climate-neutral university . You can expect numerous benefits , such as public transport season tickets and car sharing, a wide range of sports offered by the ASVZ, childcare