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Master's theses participation in national and international research projects The position comes with access to high performance computing resources and access to training opportunities within ScaDS.AI
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analyses by age, ethnicity, and index of multiple deprivation will be performed. The second stage of the study will involve the analysis of prospectively collected EQ-5D-5L data from a cohort of patients to
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universities. About the research project This PhD project is part of the interdisciplinary WASP-WISE NEST project RAM³, which aims to enable the use of recycled aluminium in high-performance applications through
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activities on fibre-coupled quantum photonic chips in semiconductor silicon carbide, which leads to high-efficiency operation. This will allow you to implement new laser pulse excitation schemes, such as SUPER
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AI training has emerged as the standard approach, which utilizes thousands of high-performance devices within a data center to collaboratively process tasks. When they are even more complex, the
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Aluminium through Machine Learning, High-Throughput Microanalysis, and Computational Mechanics” - a multidisciplinary research effort at the intersection of machine learning and materials science. This
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NEST project RAM³, which aims to enable the use of recycled aluminium in high-performance applications through machine learning, computer vision, and materials science. The focus of this position is on
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University in the Centre for Digital and Design Engineering, part of the Manufacturing, Materials and Design theme. The Centre provides access to advanced simulation, visualisation, and high-performance
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analyses by age, ethnicity, and index of multiple deprivation will be performed. The second stage of the study will involve the analysis of prospectively collected EQ-5D-5L data from a cohort of patients to
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Research Center (CRC) “Data-driven agile planning for responsible mobility” (AgiMo), funded by the German Research Foundation (DFG). This interdisciplinary center, involving four universities and the German