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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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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
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, complex dynamical systems analysis, efficient generative learning methods for statistical mechanics, highly accurate machine learning methods for quantum mechanics and inference and enhancement of cutting
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analytical sciences. We are looking for talented people to join us. Your responsibilities include: Interdisciplinary research within the project "Complex and Competing Phenomena in Recycled Flame-retardant
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PhD Position in Theoretical Algorithms or Graph and Network Visualization - Promotionsstelle (m/w/d)
evaluation methods Interactive systems for exploring complex networks Candidates interested in theoretical computer science will have the opportunity to work on topics such as graph algorithms, computational
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data mining. The group provides a strong network to local AI expertise (e. g. Hessian.AI, TU Darmstadt), large scale compute infrastructure, as well as a broad international network (Stanford, UC San