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the DFG Priority Programme “Molecular Machine Learning” and embedded in the research project “Multi-fidelity, active learning strategies for exciton transfer in cryptophyte antenna complexes”. The PhD
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(4DSTEM). This approach will combine three-dimensional charge distribution data, generated through atomistic simulations, with machine-learning-driven modelling to guide and refine the phase reconstruction
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mechanisms occurring in these materials and their synthesis over all relevant length scales (e.g., cutting-edge ab initio methods, atomistic simulation methods, multi-scale modelling, machine learning) High
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yield new insights into food-effector systems, sophisticated and tailored computational methods are needed. This project aims at combining probabilistic machine learning methods with prior knowledge in
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or machine learning. Activate map To activate the map, click on the "Show map" button. We would like to point out that data will be transmitted to OpenStreetMap after activation. You can find out more in our
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Nancy and the long-standing experience in sophisticated computer simulation studies from Leipzig, promising unique prospects in advanced education of PhD students via research into this important field
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streaming and batch processing. These efforts provide the foundation for advanced analytics, machine learning, and AI applications. The IDE Research School guides PhD researchers by offering a platform for
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, and training methods - across multiple technological platforms - photonics, electronics, biological neurons. Responsibilities and tasks This PhD project aims to develop, verify, and benchmark learning
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Research Responsibilities Conduct original PhD research on shared and remote robotic control under uncertain communication conditions, integrating passivity-based control, machine learning, and human
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), the sorption of PFAS and heavy metals onto natural nanoparticles will be investigated in situ using a dedicated field exposure method developed by our team, complemented by laboratory experiments and machine