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electrolysis and fuel cells (SOEC and SOFC). By combining numerical modeling with data-driven approaches, you will identify optimized operating conditions and strategies to improve both steady-state and dynamic
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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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and designing sustainable P2X value chains. As a PhD researcher, you will contribute to the new stack designs for high-temperature electrolysis and fuel cells (SOEC and SOFC). By combining numerical
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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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experiments Develop, optimize cellular assays and CRISPR engineering using human iPS stem cell models and differentiation systems (2D or organoids) Perform functional validation of candidate hits using
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continue reading! Join Us! Our modern society relies upon numerous electronic devices that use encryption to communicate and operate securely. However, even strong cryptography can break when the device
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, but current methods are not always efficient or optimal. The process lacks an intelligent, informed approach to selecting the best grinding parameters, which can lead to inefficient maintenance actions
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Master's degree in cybernetics, control systems, or equivalent, with a strong training in numerical optimization and optimal control. Additional training in machine learning and reinforcement learning is a
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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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than conventional structures. Superstructure optimization, which uses a predefined architecture with numerous unit operations and possible paths, offers an alternative for identifying non-intuitive