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of surface sites makes theoretical understanding difficult. This project will develop and benchmark machine learning models to predict local electronic density of states (DOS) at alloy catalytic sites
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. The postdoc will systematically model adversarial capabilities, develop proactive mitigation strategies, and evaluate their effectiveness in large-scale experimental settings. Who we are looking
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your application: Superb writing skills Experience with high-throughput simulations and materials databases Advanced heat transfer modeling, especially for TIMs and nanostructures A strong
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of numerical modelling (e.g. CFD, FEA, FSI, optimization, ML), but we are also involved in experiments and real-life monitoring to support our findings. Besides research, our division is actively involved in
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qualifications Marine biogeochemical processes Hydrodynamic processes related to ships, turbulence, or mixing Oceanographic modelling Data analysis and programming (e.g., MATLAB, Python, or R) Interdisciplinary
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are long vector/matrix multicore architectures. The goal of our team is to develop effective runtime and compiler support to program these architectures using the SYCL, OpenMP and OneDNN programming models
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attacks targeting optical infrastructure vulnerabilities. Cutting-edge ML techniques for threat modeling and detection, as well as security-enhancing network optimization approaches will be developed. Main
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must be written in English and include: A cover letter (max 2 pages) that clearly outlines your motivation, qualifications, and fit for the position. If you have not yet completed your qualifying degree