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quantify model uncertainties For further information visit our website http://www.fz-juelich.de/ibg/ibg-3/EN/Home/home_node.html or contact us via the contact form. Your Profile: Master’s degree in
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forming a moist microbial rhizosphere habitat. Your work will build on the process-based soil-rhizosphere-plant model, developed at the Agrosphere Institute, which integrates a 3D functional-structural
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temporal scales from seconds to hours and beyond. The aim of this PhD project is to build a multi-scale model linking molecular renewal to functional properties of synapses to study the relationship between
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large-scale spiking neural networks. In close collaboration with our Mod4Comp partners (DFG Forschergruppe FOR 5880), you will develop models of performance and energy to guide the co-design of software
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rules in networks of complex spiking neuron models in the application field of geolocalization: Building up simulation model for networks of complex neurons with topologies close to neuroscience models
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). These collaborations enable practically relevant and breakthrough results. This team goal requires a quantitative model describing and predicting sperm motility under various conditions. You will develop the digital
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temporal scales from seconds to hours and beyond. The aim of this PhD project is to build a multi-scale model linking molecular renewal to functional properties of synapses to study the relationship between
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Approach ( https://vhrz669.hrz.uni-marburg.de/ssf/ ). Understanding the mechanisms controlling subsurface flow (SSF) and the conditions under which it occurs remains a major challenge in hydrology and
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Your Job: This PhD project focuses on modelling and simulating future gas grids, exploring transformation pathways, and developing cross-sectoral simulation frameworks to support informed decision
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clay rocks will be evaluated. The findings will contribute to the improvement of process models for the cross-scale description and simulation of radionuclide migration in the near- and far-field of a