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and deep-learning approaches. Projects may also include detailed molecular and functional characterization of particularly exciting candidate evolutionary changes using organoid and mouse models, CRISPR
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concrete. About us Digital Structures with Mineral Materials is a new professorship at the TU Munich, focusing on the de-velopment of structural engineering, design, analysis and modelling methods
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learning-based surrogates for physical systems LLMs and scientific agents – large language models that autonomously reason, plan and execute scientific workflows AI for engineering design – LLM-driven agents
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» Modelling tools Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 15 Sep 2026 - 00:00 (Pacific/Saipan) Country Germany Type of Contract Temporary Job Status Full-time
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modeling, and scientific machine learning to enable efficient simulations of complex molecular processes across realistic time and length scales. https://doi.org/10.48550/arXiv.2604.24245 https://doi.org
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innovative AI models, we drive biomedical discovery to lay the foundation for technologies that transform medicine. Working hand in hand with experimental and clinical partners, we accelerate translation so
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-based AI for multidisciplinary tumor boards. The successful candidate will develop LLM-based pipelines, semantic harmonization, and transformer-based temporal models on a large multimodal oncology dataset
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https://www.epc.ed.tum.de/ddmm/aktuelles/article/phd-position-on-physics-informed-generative-modeling-and-multiscale-learning-m-w-d/
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AWI - Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research | Bremerhaven, Bremen | Germany | 2 months ago
implement novel parameterizations of subgrid-scale convective processes in an Earth System Model and investigate their role in Southern Ocean dynamics and global climate change. The overall objective
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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Bremerhaven, Bremen | Germany | about 1 month ago
Science (MarDATA). MarDATA’s interdisciplinary focus spans supercomputing, modelling, (bio)informatics, robotics, statistics, and big data methodologies. Doctoral researchers benefit from a structured