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analysis, and high-performance simulations? We offer a challenging PhD position in the Mathematics of Computational Science group to design and analyse novel structure-preserving methods for stochastic
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. Familiarity with dynamical systems is highly valued. Knowledge of neuroscience and muscle physiology is beneficial. Experience with MATLAB or Python for data analysis. Ability to work independently as
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Center (CoaST). These facilities are now equipped with modern graphical user interfaces, unified communication protocols, and structured data pipelines that collect and store experimental data in dedicated
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Information Benefits Challenging research tasks with real-life applications. Dynamic and innovative environment. Collaboration with national and international research networks. High degree of autonomy and
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are dynamic systems evolving over time (due to operation), this doesn’t hold. Therefore, there is much to be gained by surrogating the full structure flexibly: a generalist surrogate capable of estimating and
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conditions in dynamic and international research environment. Principal supervisor (PI) is Professor Pernille Bjørn, Department of Computer Science, pernille.bjorn@di.ku.dk The PhD programme Option A: Getting
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Materials and Devices – Structure and Function of Materials (IMD-1) to establish a data-driven, experimentally grounded workflow for rapid microstructure-property optimization in steels. The PhD student will
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outstanding students from all over the world to apply for PhD positions in our renowned PhD program. Based in Hamburg, our program offers excellent training and top-level structured supervision in climate
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addresses One Health challenges by integrating research on microbial mechanisms, microbiome dynamics in various ecosystems, and translational applications in clinical and biotech fields. DCs will benefit from
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applications as PhD Student Position (f/m/d) (Ref. 25/11) in the Leibniz Junior Research Group “Probabilistic Methods for Dynamic Communication Networks“ (Head: Prof. Dr. B. Jahnel) starting as soon as possible