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Field
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controlled instructional gradients. Your work will include designing and optimizing experimental protocols, advancing microfluidic encapsulation methods, testing novel polymer materials, and employing cutting
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properties to performance. Optimize reaction conditions and explore scale-up potential. Document experiments, publish results, and present findings at conferences. Collaborate with the Catalysis Engineering
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optimizations tailored to different environments. The optimizations range from algebraic optimizations (e.g., term rewriting) to algorithmic optimizations (e.g., group level algorithms), and to hardware
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work will focus on identifying the mathematical knowledge and properties to guide hardware optimizations tailored to different environments. The optimizations range from algebraic optimizations (e.g
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. Your work will focus on identifying the mathematical knowledge and properties to guide hardware optimizations tailored to different environments. The optimizations range from algebraic optimizations (e.g
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combines methods from ecology, industrial design, and engineering to optimize and upscale and biodegradable structures that temporarily mimic key emergent traits using industrial-scale additive manufacturing
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inspection and data collection strategies optimization, and their integration within novel data-driven risk assessment methodologies and safety certification frameworks. We focus on vertical transport (lifts
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, and portfolio optimization. Despite the growing relevance of ESG in insurance, there is no widely adopted, data-driven framework that integrates ESG metrics into customer portfolio decision-making
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responsibilities will include: - coordinating and carrying out a scientific research project. - actively participating in multidisciplinary meetings and project teams. - developing and optimizing experimental
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fundamental methods research to guide in these analytical challenges. In this PhD-project, you will propose and evaluate new AI methodology to ensure that organoid data can be used to optimally predict relevant