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approximation is the use of multilinear models which enable major reductions using tensor (multiarray) decomposition methods. Here you can develop model reduction routines for large-scale sparse power networks
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part of a DFG funded project "Decoupling above- from belowground litter decomposition and impacts on stabilization of soil organic matter with increasing aridity". Drylands cover large areas of the land
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within action field 4 and other action field of the ReGenFarm. Your tasks in detail: Extend a bioenergetic process-based model to include the decomposition of specific biomolecules and their effects
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, using techniques such as: High-dimensional data mining Tensor decomposition Causal inference Statistical process modeling Machine Learning Applications include public transport, private vehicles, traffic
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spectrometry (LA-ICP-MS) for biomedical samples within the framework of the Collaborative Research Centre SFB 1340 “Matrix in Vision“ Planning and realisation of measurements with LA-ICP-MS in cooperation with
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large multi-dimensional datasets using statistical tools such as positive matrix factorization (PMF) and cluster analysis Investigate the influence of different urban emission sectors on atmospheric
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matrix factorization (PMF) and cluster analysis Investigate the influence of different urban emission sectors on atmospheric composition Present your results at international conferences and publish in
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certain class of cyclic aromatic compounds that have been first proposed by Heilbronner in 1954, but still are elusive till date. By combining the expertise of synthesis, matrix isolation, on surface
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cyclacenes, a certain class of cyclic aromatic compounds that have been first proposed by Heilbronner in 1954, but still are elusive till date. By combining the expertise of synthesis, matrix isolation
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adhesives. In the projects, we investigate the material and joining properties, as well as the processes for the successful application of the adhesives. The matrix shingle technology is particularly suitable