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demands. To break this bottleneck and cut simulation time by orders of magnitude, you will design and implement surrogate models that learn the behavior of full‑physics codes using modern machine‑learning
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Particle Acceleration is looking for a PhD Student (f/m/d) Multimodal Reconstruction of Laser-Electron Accelerator Phase Space using Physics-Informed Deep Learning. Your tasks Understand the physical process
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., (2025) Molecular Plant. Reference: https://www.sciencedirect.com/science/article/pii/S1674205225000280 Tasks include cloning and construct creation experimental design plant growth and survival assays in
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molecular processes, how disease mutations would disrupt PPIs, and in guiding design of binders with therapeutic potential. The ways by which proteins can interact with each other are highly diverse, yet this
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according to the German TV-L13 65% and additional benefits such as a pension plan. Although the position is fully funded, we fully support your applications for career advancement grants or PhD research
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applications for a PhD Student or Postdoc Position (f/m/d) for any of the following topics: Combining non-equilibrium alchemistry with machine learning Free energy calculations for enzyme design Permeation and
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play a central role in this interdisciplinary initiative. They will: Develop and apply machine learning (ML) methods – including surrogate modeling, feature extraction, and inverse design algorithms
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interdisciplinary collaboration. That’s why our projects are designed specifically to connect diverse scientific fields and foster cross-institutional collaboration, enabling you to benefit from the combined
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collaborations. That’s why our projects are designed specifically to benefit from collaboration among scientific experts from various fields and disciplines, enabling you to benefit from the combined supervision
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play a central role in this interdisciplinary initiative. They will: Develop and apply machine learning (ML) methods – including surrogate modeling, feature extraction, and inverse design algorithms