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response data with preclinical model testing to create the world′s largest metastatic pRCC database. Heidelberg University leads the multidimensional data integration task, focusing on centralized data
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-0831 Description of Work: At the Digital Twin Innovation Hub, we are developing infrastructure for the construction, simulation, analysis, and visualization of a human immune system model that represents
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: • Foundational research on large-scale / foundation models and agentic architectures for autonomous social-science reasoning and planning. • AI Social Scientist / AI Historian research: causal reasoning methods
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position (m/f/d) in multiscale, multiphysics, mathematical modelling of plant morphogenesis as soon as possible. Description of the project Plant growth is a complex hydromechanical process in which cells
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engineering schools in the world. For more details, please view https://www.ntu.edu.sg/mae/research . We are seeking to hire a Research Engineer to conduct interdisciplinary research on risk modeling, analysis
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Biotechnology and Bioprocesses, Membrane Technology, Chemicals and Materials, Resource Recovery, and Modelling & Artificial Intelligence. By harnessing its cross-cutting, interdisciplinary, and transformative
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Biotechnology and Bioprocesses, Membrane Technology, Chemicals and Materials, Resource Recovery, and Modeling & Artificial Intelligence. By harnessing its cross-cutting, interdisciplinary, and transformative
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project aims to unravel the molecular mechanisms underlying these processes in lactating mammary epithelial cells. Using a cutting-edge lactation organoid model developed in our laboratory, combined with in
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experiments in gelatine (https://doi.org/10.5194/egusphere-egu25-9211). This model will be tested with analogue experiment results from the MAGMA Lab, run by other members of the project team. The second
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EpiFlaMe Consortium (located at University of Salzburg, University of Linz, and Medical University of Vienna) | Austria | 3 days ago
The project focuses on understanding memory processes in epithelial cells upon inflammation and cancer development using multi-omics profiling, computational modeling, and dedicated experimental coculture