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reputation for carefully designed and precisely controlled experiments, high quality temporally and spatially resolved field experiments using particle image velocimetry combined with synchronised measurements
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for the efficient formation of high-value compounds. Advanced NMR methods and computational data analysis will be compounded to devise novel reactions towards pharmaceutical precursors, polymer building blocks and
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engineering, and hyperparameter tuning to produce resilient and high-performing models. · PhD in Computer Science, Machine Learning, Mathematics, Physics, Statistics, or a related field Strong track record
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Description The Graduate School Scholarship Program(GSSP) of the German Academic Exchange Service (DAAD) is offering two (2) doctoral scholarships to earn a PhD within the framework of “Ancient
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funding affect the subsequent performance of firms and scientists, in terms of outputs such as the number of papers, products, patents, etc. (Can an optimal applicant template be developed by training
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on Artificial Intelligence (AI), Deep Reinforcement Learning (DRL), and Predictive Maintenance for optimizing wind turbine performance and reliability. This research will develop an AI-powered wind turbine
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enhance system reliability and safety, aligning with the UK’s NetZero targets. Aim You will have the opportunity to build a high-fidelity process simulation and perform experimental validation to assess
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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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turn fundamentally alter the functioning of ecosystems. Alpine and arctic ecosystems have remained relatively natural so far, but are especially affected by these changes as they are warming faster than
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the health and performance of humans in several situations (e.g. firefighters, who are exposed to extreme heat, or older adults who are exposed to heat stress during heat waves) by modeling the environment