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and Sciences. Application Deadline: May 1, 2026 CORE DUTIES: Participating in the planning and performing/conducting research tasks by applying basic knowledge and understanding of scientific theory
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Experienced in one or more ML/AI techniques, such as reinforcement learning, federated learning, natural language learning, graph neural network Experience working on cyber-physical power systems, ideally
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institutional, historical or technological lines; (iv) Teaching experience in some the following subjects: theory, history, and methods of media and creative industries; comparative cultural policy in East Asia
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Jülich, which is dedicated to pushing the boundaries of data science theory and application. Our research spans from use-inspired, method-driven theory to application-driven research. Please find more
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techniques more interpretable and biologically meaningful in their application to neural population coding. As a starting point, we will build upon recent advances in graph neural networks (GNNs), particularly
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impactful research on digital discourse and linguistics, digital humanities, as well as theories of aesthetics and politics, significantly contributing to our understanding of language, culture, and
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to neural population coding. As a starting point, we will build upon recent advances in graph neural networks (GNNs), particularly those described by which offer a promising architecture for modelling
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Jülich, which is dedicated to pushing the boundaries of data science theory and application. Our research spans from use-inspired, method-driven theory to application-driven research. Please find more
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Simulation – Data Analytics and Machine Learning (IAS-8) at Forschungszentrum Jülich, which is dedicated to pushing the boundaries of data science theory and application. Our research spans from use-inspired
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Applied statistics Network routing Agent-based simulation Behavioral economics Game theory Decision theory Machine learning Artificial intelligence Where will I be located? Both local and remote