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implemented to address this – from family-centred interventions, to resource provision. However, impacts are often distal and diffuse, making it difficult to make evidence-based judgements on which initiatives
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behaviours of multi-agent systems in response to changing internal states and external environmental conditions. Both traditional model-based approaches and modern learning-based control techniques will be
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to traditional remediation approaches. Where to apply Website https://www.sckcen.be/en/thesis-and-internship-topics/circular-and-nature-based… Requirements Research FieldBiological sciences » Biological
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to changing internal states and external environmental conditions. Both traditional model-based approaches and modern learning-based control techniques will be employed to achieve an appropriate trade-off
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university. We are willing to support applications related to our research on complex systems, network and data science, agent-based models, statistical physics, or computational and mathematical modelling
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, Attacks, and Defenses”. Your work assignments Large language model (LLM) agents represent the next generation of artificial intelligence (AI) systems, integrating LLMs with external tools and memory
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the European Research Council (ERC-CoG2025). Main tasks: This project aims to develop smart imaging agents based on single particle tracers to image alterations of the blood flow dynamics in cancer by positron
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background in (not necessarily all) the following fields: nonlinear PDEs, functional analysis, numerical analysis, PDE-based modeling and numerical simulations excellent command of the English language ability
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fields: nonlinear PDEs, functional analysis, numerical analysis, PDE-based modeling and numerical simulations excellent command of the English language ability to teach in German and English We offer
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-preserving models that implement synthetic data; and developing generative AI models for accelerating data sharing using synthetic data, agentic AI synthetic data, differential privacy, and federated learning