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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Dresden, Sachsen | Germany | about 1 month ago
employment. Starting date: 01.04.2026 Job description:PhD Student (f/m/d) in Quantum Algorithms for Droplet and Bubble Oscillation Dynamics Modelling With cutting-edge research in the fields of ENERGY, HEALTH
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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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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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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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, 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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such as scalable identification algorithms, uncertainty quantification, and the integration of learning-based models with formal verification. We offer a supportive, inclusive, and collaborative research
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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