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. MINDnet aims at addressing the challenge through a holistic optimization - from individual computing devices to the overall architecture, including a focus on applications, and training methods - across
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local activation), multi-timescale adaptation (local memory), and stimulus-specific adaptation (multi-task processing). While the co-optimization of dendrite-inspired functional circuits with emerging
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project, you will help design, simulate, and optimize these next-generation communities — making clean, local, and intelligent energy systems a practical reality. Your key responsibilities include
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, optimize and extend existing setups, develop a novel setup to perform an absolute radiometric calibration Perform a line-of-sight calibration to precisely align the instrument’s viewing geometry with
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the inductive heating of heterogeneous catalysts as an integral advantage. Your focus will be on the investigation, development, and optimization of this new process in a continuously operated reaction
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-efficient processing capabilities. MINDnet aims at addressing the challenge through a holistic optimization - from individual computing devices to the overall architecture, including a focus on applications
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linkages based on numerical simulations and to transform them into AI- and ML-ready information to develop and implement an indirect inverse optimization framework to identify microstructures that exhibit
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on model surfaces In situ and operando (surface) X-ray scattering studies of catalyst/polymer interfaces Design, optimization, and testing/benchmarking of reactors for in situ and operando studies
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-following inverters. Implementing and optimizing scalable algorithms for transient and stability analyses on HPC architectures (CPU, GPU, hybrid). Enhancing the numerical robustness and efficiency of existing
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energy system models based on the institute`s own open-source FINE framework https://github.com/FZJ-IEK3-VSA/FINE. Your tasks in detail: Implementing geothermal plants with material co-production in