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image sequences. As a benchmark, end-to-end deep learning models will be developed using raw image data. In parallel, shallow learning models (e.g., Gaussian processes) will be explored based on insights
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Institute) Besides the project leaders, the Dynamigs team includes several senior and postdoc researchers. As a part of this project, you will conduct quantitative research on demographic behaviour
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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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-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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many real-world applications, finding a solution requires high-performance computer clusters that consume large amounts of energy and run for a long time. Our project aims to create a radically new
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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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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