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farm management through innovative sensing technologies, advanced modeling, and intelligent automation. This PhD project contributes to PhenoRob’s initiative to develop digital twins for agroecosystems
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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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modelling, analysis of complex dynamical systems, simulation, analysis of large-scale datasets with machine learning methods, and software development are beneficial Good organisational skills and ability
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development, version control systems, Linux environments, and SSH. Very good command of written and spoken English (at least B2 level according to the CEFR: https://go.fzj.de/languagerequirements ), ideally
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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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tasks include: Development and optimization of interfaces and APIs for the integration of heterogeneous energy system data Implementation and maintenance of automated data processing and transformation
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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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Your Job: As part of this master`s thesis, the agent-based energy market simulation ASSUME should be expanded to include the local neighborhood. The goal is to further develop the existing
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candidates which are explored in more depth. In particular you will work on the extension, development and analysis of new quantum algorithms for near-term and fault tolerant quantum computers for drug
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the mechanisms underlying yield decline in continuous wheat systems. Your tasks: Assist with greenhouse experiments using rhizobox systems to study wheat root development Conduct experiments under different crop