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Field
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-MID prototyping and performance optimization of structure-embedded sensors and nanogenerators. Depending on applicant’s skillset the research objectives may include implementation of AI-assisted in
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optimization strategies to maximize yields of desired products. A key aspect of the project is understanding and improving catalyst stability, including identifying deactivation mechanisms and developing
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investigates how to adapt, modify, and optimize decentralized nature-based solutions (NbS) and green-grey hybrid infrastructure—encompassing sanitation, drainage, and flood mitigation. The candidate will address
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methods to automate the mechanical design process and structural validation of beams used in the ship's equipment. • Develop methods for optimizing the design of beams. • Integrate the developed methods
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while maintaining computational efficiency through lower-fidelity simulation of non-critical regions, (ii) virtual sensing techniques for load and stress estimation from limited and optimally placed
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crack initiation and propagation; Development and validation of a digital twin with an appropriate level of maturity; Proposal and evaluation of new cluster architectures; Validation of optimized
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-modality models Knowledge in deep learning optimization, such pruning and quantization Strong academic writing skill Personal characteristics To complete a doctoral degree (PhD), it is important that you are
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the bearing. To optimally re-lubricate, it is vital to understand this mixing process. Currently, the scientific knowledge of re-lubrication is non-existent. This project will build new knowledge on several key
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and prothrombin. Wet lab production and screening of the aforementioned binders. Optimization of heterobispecific Fc format using protein engineering focusing on humanization and improved stability
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with advanced photoreactors, modular LED light sources, inline analytics, and machine-learning algorithms for the autonomous optimization of photocatalytic reactions. Research will address key challenges