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Field
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The Fraunhofer IEE in Kassel conducts research in the fields of energy economics and energy system technology, focusing on: energy informatics, energy meteorology and geoinformation systems, energy
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the areas of ‘Process Sensors and Systems Engineering’, ‘Material Analytics’ and ‘Computational Methods’. With our expertise in data science, modelling and systems engineering, we develop tailor-made
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to model and analyse the intrinsic complexities of these systems. This research direction requires advancements in modern probabilistic tools, including spatial random graphs, random walks, and Markov chains
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energy system model workflows Your Profile: Master’s degree in computer science, data science, natural sciences, economics, engineering, mathematics or a related field of study Huge interest in data
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highly motivated doctoral student to join an ambitious project aimed at building machine and deep learning models to study the genetics of human disease. Funded as part of the Helmholtz AI program, the
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, probabilistic models Representation learning, self-supervised learning, foundation models Data analysis, non-linear statistics, knowledge management Your profile PhD in Computer Science, Bioinformatics
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research program. What will be your tasks? This position will be part of the international SkaMix Consortium with partners from Norway, Sweden, Denmark, The Netherlands and Germany with the aim to identify
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Max Planck Institute for the Structure and Dynamics of Matter, Hamburg | Hamburg, Hamburg | Germany | 30 days ago
develop state-of-the-art theoretical and computational methods to model strong light–matter coupling in and out of equilibrium, across gaseous, liquid, and solid-state systems. Key responsibilities The PhD
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strengthen them. In particular, the successful candidate is invited to join the newly established Collaborative Research Center CRC 1720 “Analysis of criticality: from complex phenomena to models and estimates
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the variation of materials. Corresponding models are developed with which the mechanical stresses of the interconnection are determined in order to identify optimizations in the process control and material