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& Emergent Behaviour in Complex Networks“. Here, we intend to investigate how structural properties of complex networks influence information and opinion dynamics. Our goal is to gain a deeper understanding of
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at the IMPRS-LM aim to dissect the spatial and temporal organization of biochemical networks in the cellular environment. The IMPRS-LM provides a unique graduate training program that equips students with
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that exhibit emergent turbulent behaviors, and (2) disordered optical media that process information through complex light scattering patterns. Using advanced imaging, machine learning techniques, and real-time
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, these models often use simplified, linearized assumptions, limiting their capacity to capture the nonlinear complexities inherent in real-world hydrological processes. Recently, there has also been the branch
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few kilometers using new computer science methods, particularly machine learning. This involves the analysis of very complex spatiotemporal phenomena, especially so-called submesoscale processes
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years of professional experience Experience in programming (Python, Linux-Shell, git) and Linux system administration Several years of professional experience with network or server infrastructures. HPC
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candidate of the Graduate School LSM, you will be part of a vibrant, diverse, active, and truly international research community. We value interdisciplinarity, as it allows you to expand your research network
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(NGS) technologies, including single-cell sequencing, to interrogate transcriptional networks. A central focus of your work will be the systematic analysis and interpretation of multi-omic datasets
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. The position is within the Math+ project "Information Flow & Emergent Behaviour in Complex Networks“. Here, we intend to investigate how structural properties of complex networks influence information and
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part of the MARDATA doctoral network, the project “AI-derived thermodynamic parameters for aqueous modelling (AI-queous)” invites applications for a PhD position at the intersection of Computer Science