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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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aims to develop responsible transport appraisal methods that consider multiple performance metrics simultaneously, with a special emphasis on fairness to weigh different circumstances, constraints, and
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-time 65%) in the DFG-funded Integrated Research Training Group (RTG) Beyond Amphiphilicity – RTG 2670: Self-Organization of Soft Matter via Multiple Noncovalent Interactions . The position is funded from
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TV-L, part-time 65%) in the DFG-funded Integrated Research Training Group (RTG) Beyond Amphiphilicity – RTG 2670: Self-Organization of Soft Matter via Multiple Noncovalent Interactions . The position
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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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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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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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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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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