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Description Are you interested in the development of future materials, the chemistry of crystalline molecular assemblies, or chemical reactions catalyzed by unique atomic arrangements? Do you prefer
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to understand, predict, and treat diseases. You will work with multimodal biomedical datasets including omics, imaging, and patient data and apply cutting-edge AI models such as graph neural networks, transformer
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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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Optional requirements: background or experience in protein biochemistry and molecular cell biology research communication skills in German (can, alternatively, be learnt on the post) We offer: integration
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available on site for the development of suitable radiotracers. One focus of the work is on the use and evaluation of large tomographic data sets to derive parameter data for reactive transport modeling
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: Prof. Dr. Steven Travis Waller, Chair of Transport modeling and simulation, and co-supervised by at least one additional professor, plus an international tutor of the CRC Requirements: excellent
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civil/electrical/control engineering or mathematics or related study programs with a solid basis in choice modelling and/or reinforcement learning, with knowledge of MATSim is advantageous. Description
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phenomena such as the spread of misinformation or the formation of filter bubbles. For this, we rely on rigorous probabilistic methods to model and analyse the intrinsic complexities of these systems
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Description Are you interested in developing novel scientific machine learning models for a special class of ordinary and differential algebraic equations? We are currently looking for a PhD
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kinetic modeling Experience with (or willingness to learn) 3D modeling, CAD software, and 3D printing What We Offer: TV-L (E13, 67%) collective agreement ( Current TV-L pay table [pdf-Datei] ) A three-year