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tools. In this PhD position, you will investigate the use of logic-based methods to provide decision support for the process of designing electromechanical systems. Here, the focus is not on the system
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-making (e.g. during operation, but also during design) to prevent over-consumption of fatigue life while balancing optimal production. The monitoring of fatigue loads along the entire substructure is a
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efficient than digital computer and previous experimental implementations. This work is both experimental, numerical and theoretical in nature. You will be selected by the Applied Physics research group
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Directed Energy Deposition (DED) process for metallic components. The PhD candidate will focus on edge computing and the application of AI for data analysis and for identifying correlations with ground truth
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characteristic of damaged gears or bearings. Furthermore, the increasing decentralization of wind farms necessitates robust and efficient on-site data processing capabilities. This PhD project will address
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cells, embryo models and human embryos, with a focus on understanding how cell stress impacts these processes. During your PhD, you will work very closely with a postdoctoral fellow that will be carrying
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of UHPC behavior. By monitoring damage processes at an early stage, material optimization can be achieved, and prompt maintenance actions can be taken to prevent compromised performance, ensuring safety and
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and concerns about the dominance of the highly educated. Against that background, this PhD project aims to achieve a better understanding of the particularities of education-based status processes by
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for the future design of urban transformation processes, ensuring that best practices can inform future policy and planning. The expected results are: 1) Critical analysis of the impact of mobility campaigns
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offshore wind farms are coming online with tighter fatigue designs and more aggressive control strategies, your research will seek to assist decision-making (e.g. during operation, but also during design) to