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for the clean, efficient, and fuel-flexible use of ammonia-based fuels in gas turbines. The research approach combines high-fidelity numerical simulations and turbulent combustion modeling. A closely related
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Variational Autoencoders or GANs, to efficiently analyze high-dimensional design spaces even with sparse data. Simulation setup: you create parametric geometries and build simulation chains as "virtual test
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modeling, and scientific machine learning to enable efficient simulations of complex molecular processes across realistic time and length scales. https://doi.org/10.48550/arXiv.2604.24245 https://doi.org
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disabled persons or persons of equal status will be given priority in accordance with SGB IX. The above position is one of 15 doctoral candidate positions of the MicroMan4Health doctoral network (https
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thermoacoustic instabilities in hydrogen-fueled combustion systems. The project combines the expertise of 12 European research institutions in advanced experiments, high-fidelity simulations, theory, automatic
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accelerator physics and deep knowledge in RF technology, preferably x-band Experience with simulation codes, such es elegant, to model the beam dynamics Hands-on experience building accelerators Experience with
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-Augmented Generation (RAG) or multi-agent systems. Experience in preliminary engine design, with the GTlab framework or comparable simulation-based design environments, as well as in the conception
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integration Strong programming skills, preferably in Python, for data analysis, simulation, and instrument control Proven ability to work independently on a complex technical project, from conceptual design to
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Max Planck Institute for Chemical Energy Conversion, Mülheim an der Ruhr | M lheim an der Ruhr, Nordrhein Westfalen | Germany | 8 days ago
vitae with the contact details of three referees, and a copy of your degree certificate. If we have aroused your interest, then please send your application preferably in digital form by October 2, 2026
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Lukas Stelzl (JGU Mainz) within CRC/SFB 1551, we now want to rebuild active transcriptional condensates from the bottom up - with molecular simulations and C. elegans experiments as direct partners