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Field
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(e.g., transportation networks, manufacturing systems, and truck routing). Assessing the relevance of the intake fraction (i.e., exposure efficiency) of major emission sources as a critical metric for
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limited understanding of how tumors systemically impair immune responses. Meanwhile, traditional animal models often fail to capture the complexity of human immune-cancer interactions. This position
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. The successful candidate will develop advanced machine learning (ML) models to automate and optimize retrosynthetic analysis, facilitating the discovery of efficient and sustainable synthetic routes for complex
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systems (ITS). In particular, the successful candidate will conduct cutting-edge research in: Developing physics-informed neural networks (PINNs) for complex dynamical systems modeling and observer design
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are working to advance the understanding of complex systems through the lens of networks, and to apply this knowledge to solve real-world problems in a wide range of fields, including urban science, public
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Neuroscience (IoPPN). The centre aims to better understand the complex interrelationships between society and mental health, with a commitment to: Ensure that the impact of social context is central to how we
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complex behaviours, including learning, in the small invertebrate model organism C. elegans. We have recently discovered a range of novel dopamine receptors in C. elegans and found that different receptors
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of the Microverse” (www.microverse-cluster.de ), the CRC/Transregio 124 “Pathogenic Fungi and Their Human Host: Networks of Interaction” (www.funginet.de ) funded by the Deutsche Forschungsgemeinschaft and the
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data analysis experts. The main tasks include the analysis of complex biomedical data using modern AI methods, as well as the development of novel machine and deep learning algorithms to understand
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(e.g., transportation networks, manufacturing systems, and truck routing). Assessing the relevance of the intake fraction (i.e., exposure efficiency) of major emission sources as a critical metric for