42 advance-soil-structure-modelling Postdoctoral positions at Technical University of Munich
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at the Technical University of Munich (TUM), led by Prof. Massimo Fornasier, is seeking outstanding candidates to join the newly established research team for the ERC Advanced Grant project “Nonlinear Evolutions and
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management. Our group combines empirical work (with experiments in the field and in the lab) and modelling techniques. The focus of this postdoctoral position is the generation of empirical datasets
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, climate and earth system modeling, soil parameter mapping, and multi-sensor segmentation, together with our partners at renowned international and national institutes such as Bonn University, Alfred Wegener
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(with experiments in the field and in the lab) and modelling techniques. The focus of this postdoctoral position is the generation of empirical datasets for livestock systems in East Africa, and in
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)confinement in string-net models - Quantum field theory, lattice QCD To apply, please send your application via email with the title “PostDoc application” or “PhD application” to application@zachegroup.com
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insulators or 2D-materials and their heterostructures). • Quantum sensing, including low-temperature scanning NV magnetometry. • Strong correlation and many-body phenomena in 2D-quantum materials. • Advanced
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' prognosis or treatment decisions. For modeling, we use both public and proprietary clinical and research data greatly enriched by our own repository of digital pathology images. A further focus lies on
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of the research group ‘Crop Physiology’ is to understand the physiology of plants down to the structure and function of genes and proteins. Thereby, relevant mechanisms are identified, which allow optimizing
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located on the new Heilbronn campus (not in Garching / Munich!) Your tasks Graphs are a fundamental data structure and are commonly used to model relationships between data points such as links between web
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communication system are modeled using information theory. We wish to investigate how interleaving can reduce the overhead and computational load due to coding coefficients required in classical linear random