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improve models and codes for assessment of the liquid source term during severe accident (SA) of LWR systems. In particular, research will include assessment of the characteristics of the containment water
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mathematics, ecology, history, climatic and medical sciences in collaboration across multiple institutes. An integral part of the project is to develop process-based eco-epidemiological models considering
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remote brain areas in vivo in animal models that underlie plasticity in the prefrontal cortex of mice. We will focus on neuronal micro- and macro-circuits that influence our feeding behavior, which
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language model–driven agents to autonomously configure and deploy 6G and cloud functions. The project leverages digital twin environments and validation frameworks to ensure reliable, secure, and
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combination with machine learning and/or data mining techniques • Explainable AI/ML using visualization • AI/ML-empowered visual analytics of multivariate networks (network embeddings, …) • Large Language Model
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. The postdoc will systematically model adversarial capabilities, develop proactive mitigation strategies, and evaluate their effectiveness in large-scale experimental settings. Who we are looking
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that combine network-level protections with AI- and system-level adaptivity. The postdoc will systematically model adversarial capabilities, develop proactive mitigation strategies, and evaluate
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, and agent-based modelling have paved the way for innovative collaborations between social scientists and computer scientists that jointly seek to answer fundamental questions of the social sciences and
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ecosystem functioning. The postdoctoral project will focus on analyzing and modeling tree architecture in relation to forest vitality and stress predisposition. The work will combine 3D structural data (from
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groundbreaking work on enzyme-triggered electrode fabrication in animal models (Strakosas et al., Science, 2023; https://doi.org/10.1126/science.adc9998 ), this project leverages enzymatic polymerization to create