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Field
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than conventional structures. Superstructure optimization, which uses a predefined architecture with numerous unit operations and possible paths, offers an alternative for identifying non-intuitive
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-duration energy storage. The approach is to use hierarchical structures, i.e. complex material layers that can be optimized to specific battery chemistries and flow phenomena from the microscale up
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adaptation and learning from their experiences. Using a combination of theory, numerical experiments and precision desktop experiments, we will create 3D materials with self-adapting elastic elements
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mechanical motion into electricity; - An intelligent electronic control system, enabling optimized regulation of the thermodynamic cycle. Within the CALIFORCE3 framework, the REMLA system will be integrated
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Dresden, Sachsen | Germany | 8 days ago
planned to start on February 1, 2026. An earlier start is negotiable. Your tasks # Further development and optimization of spectroelectrochemical methods # Electrochemical synthesis of Tc inorganic
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-Performance Computing for Exascale" contributes to the design and development of numerical methods and software components that will equip future European Exascale and post-Exascale machines. This program is
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worldwide in industrial and academic research labs for device and material optimization as well as for the study of device physics. Leading manufacturers and academic institutes rely on our tools for electro
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. Perform sensitivity analysis, parameter estimation, and uncertainty quantification utilizing multiscale experimental data. Collaborate closely with experimentalists to iteratively refine models and optimize
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structures. Other aspects of the research include a numerical framework for the sensitivity analysis to facilitate design optimization and experimental system identification. Information and application
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-assisted simulation framework by providing accurate high-fidelity numerical data for training and validation of surrogate models for multi-disciplinary design and optimization. · Participating in