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an innovative reconstruction algorithm and methods to correct factors impacting the quantitative accuracy of PET images. Our recent research has focused on dual-tracer PET imaging, in which two radiotracers
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reconstruction to overcome these challenges. Your tasks - develop physics-informed, self-supervised learning approaches for phase retrieval - implement reconstruction algorithms on HPC clusters for large-scale
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tomography and local adaptive reconstruction to overcome these challenges. Your tasks develop physics-informed, self-supervised learning approaches for phase retrieval implement reconstruction algorithms
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Approach ( https://vhrz669.hrz.uni-marburg.de/ssf/ ). Understanding the mechanisms controlling subsurface flow (SSF) and the conditions under which it occurs remains a major challenge in hydrology and
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, enabling algorithm–circuit co-optimization across the computing pipeline with respect to key metrics such as power consumption, computational delay, and area efficiency. Beyond circuit prototyping
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dynamic systems, control engineering, and applied mathematics? Do you want to develop cutting-edge control algorithms for the security and resilience of cyber-physical systems? We welcome you to apply for a
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excitations and excitonic effects using advanced Wannier-based methods * Quantum transport in polymer materials with electron–phonon coupling Full details and application instructions: https://www.ch.nat.tum.de
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-related traits, and heterosis. In the era of large population size and dense genomic data such as whole-genome sequencing, new algorithms are needed to remove the bottleneck of computational load for such a
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. You will contribute to developing datasets, baseline models, personalized learning engines, reasoning-graph representations, cross-domain mapping algorithms, and RLHF-style feedback loops that improve
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Technology, Dep. ETI / Embedded Systems, we are looking for a researcher as of the 01.04.2026. Your tasks: Development of architectures and algorithms for adaptation of time-triggered systems based