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PhD Stipend in Digital Twin Modelling and Multi-Timescale Optimization of Electrolysis Systems Apply Vacant position PhD Stipend in Digital Twin Modelling and Multi-Timescale Optimization of
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PhD Stipend in Dynamic Modelling, Simulation and Optimization of Power-to-X Processes Apply Vacant position PhD Stipend in Dynamic Modelling, Simulation and Optimization of Power-to-X Processes
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renewable energy. You will investigate quantum and hybrid quantum–classical methods for power system analysis and optimization, with emphasis on their practical performance and suitability for real
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work at the intersection of thermal energy systems, machine learning and scientific AI, system modelling and identification, as well as optimization and control. Your work will focus on developing
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nutrients. Integrate advanced sensors (e.g., spectral, LiDAR) and simulation tools to guide robotic actions for yield optimization and enhanced biodiversity. Team and role You will: Be a core member
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and Artificial Intelligence. Experience with one or more of machine learning, wireless communications, signal processing, multimodal sensing, robotic perception, optimization, or control will be an
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challenges facing contemporary port ecosystems: how ports can develop new strategic roles in support of the green transition. The project will explore how ports move beyond their traditional functions and
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should not be discouraged from applying. Job description The postdoctoral researcher positions are fixed-term academic research positions. CEPDISC functions as a research team, and the selected
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surface dynamics Develop and apply Python-based image/data analysis tools for large time-resolved TEM datasets Establish quantitative links between 3D atomic structure, dynamics and catalytic functions of