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modelling and improving Earth System Modeling by better merging of measurement data and model simulations. This PhD project focuses on improving how we estimate key parameters in land-surface and ecosystem
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geometries. Current simulation-based approaches require complex 3D meshes and are often too slow for practical medical use. This project aims to create accurate and rapid surrogate models by combining physics
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the use of large language models to support neural network design and data preprocessing. The position involves close collaboration with experts in cardiovascular simulation and Scientific Machine Learning
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physics-aware simulations of growing cell populations, including their spatiotemporal manipulation in microfluidic environments Design and implement reinforcement learning algorithms for control and
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(transcript of records), a copy of your Master thesis (or a draft thereof), published articles or other relevant material such as letter(s) of recommendation (if applicable). Our Offer: We work on the very
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documents to the DAAD portal by the application deadline. The DAAD portal closes at 24.00 hrs. (CET or CEST) on the last application day. If possible, please do not send your application on the final date in
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, and therefore expressly welcomes applications from women. Please send your application by December 31, 2025 with the subject SuReMo CBR via E-mail to: bew_cbr@cs.tum.de. Technische Universität München
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opaque “black boxes,” we will integrate post-hoc explainability tools such as SHAP values (SHapley Additive exPlanations) Thrust C: The utility of all developed methods will be rigorously evaluated using
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any technical questions or problems your local information and advice centres could not help you with, please do not hesitate to contact portal@daad.de via e-mail. Please consider possible processing
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. Where to apply E-mail dominik.munz@uni-saarlan.de Requirements Research FieldChemistry » Molecular chemistryEducation LevelMaster Degree or equivalent Skills/Qualifications - Specific Requirements