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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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/datathons. Send your application if you can see the potential in thinking simulations and data together and if you are ready to conquer the data driven challenges of tomorrow! Where to apply Website https
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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