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leadership to align team outputs with program and enterprise-level modeling strategies. • Advocate for continuous improvement in modeling practices, tools, and methodologies. • Contribute to the definition and
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Dynamic skewness in longitudinal data models School of Mathematical and Physical Sciences PhD Research Project Self Funded Dr Miguel Juarez Application Deadline: Applications accepted all year round
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uncertainties about viable business models and reward structures. Your job This postdoctoral position is part of ReGeNL , a large national inter- and transdisciplinary research programme aimed at accelerating
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motivated candidates interested in (models of) quantum computing and the theory and implementation of programming languages. The ideal candidate has an MSc degree in computer science, mathematics, physics
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information is stored and retrieved, and how language use is intertwined with memory during communication. The model will be hybrid, merging linguistic factors uncovered in computational and theoretical
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The world is dynamic, in constant flux. However, machine learning typically learns static models from historical data. As the world changes, these models decline in performance, sometimes
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to the interdisciplinary Wicked Problems (WiP) framework in the undergraduate program. This role integrates mathematical modeling, numerical simulation, and decision optimization to help students understand, abstract, and
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, it is a globally respected institution that also has outstanding economic significance for the Rhine-Neckar metropolitan region. At the Interdisciplinary Center for Scientific Computing (IWR
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, membranes and advanced electrochemical systems. Collaborate with AI and computational science teams to accelerate discovery using machine learning, large language models (LLMs), and large quantitative models
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The candidate based at CWI will have either a computer science or mathematics background, with a strong affinity for energy systems modeling, or an [electrical] engineering background, but with