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databases, and machine-learning-augmented life cycle assessment (LCA) tools to generate energy and mass balances for key production processes. A significant part of the project will be linking
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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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. At the same time, data-driven methodologies and machine learning offer new opportunities for optimal traffic management strategies but often they lack physical intuition, which creates obstacles towards large
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achieve. Our research aims to identify and address the energy and carbon inefficiency of modern computer networks. Projects in this area are inherently multidisciplinary as energy consumption is affected by
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, has created two exciting PhD positions within the Block Research Group. These positions provide an exceptional opportunity to contribute to pioneering zero-carbon concrete structures. Candidates will