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Efficient and Reliable Numerical Solution of Dynamic Optimization School of Electrical and Electronic Engineering PhD Research Project Self Funded Dr Yuanbo Nie Application Deadline: Applications
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. This project is intended to perform numerical studies and develop a methodology for the numerical analysis aimed at the effective damping of resonance regimes in bladed disks of gas-turbine engines using
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technology with potentially significant impacts on numerous industrial sectors. At Fraunhofer IKS, we engage in a variety of projects aimed at developing robust and reliable applications of quantum computing
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-of-the-art sparse algorithm in matrices, tensor and networks for large-scale numerical, scientific and AI models and disseminating findings through publications and presentations in top-tier peer-reviewed
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to numerous preclinical research projects focused on the development of novel molecular magnetic resonance imaging (MRI)-based techniques for early detection, disease phenotyping and monitoring treatment
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solid particle transport. The successful candidate will contribute to the creation of an AI-optimized platform capable of achieving up to 50× speedups in simulation performance, enabling real-time, energy
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approach may include mathematical modelling, differential equations, dynamic programming, optimal switching theory, classical optimization, numerical solution methods, and programming. You will carry out
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advancements and practical implementations optimized for modern HPC systems. The postdoc will primarily contribute to one or more of the following research areas: Development of efficient numerical linear
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division at the department of Electrical engineering at Chalmers. Here, a team of PhD students, post-docs and senior researchers are working on modeling and numerical optimization of problems in the areas
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control, as well as machine elements and design optimization. The research rests on theoretical, numerical and experimental investigations of phenomena that are most often highly cross-disciplinary and span