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, machine learning or similar. Alternatively, you have gained essentially corresponding knowledge in another way. The applicant is expected to have good knowledge of computer science, mathematics, algorithms
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tailored surveys for enriching the understanding of the mixed system. The behavioural understanding on the demand side will provide information to the supply side, such as the trade-offs between different
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exposed to Bayesian optimization to find the optimal set of parameters that improve process performance and material quality. Secondly, different machine learning strategies based on traditional supervised
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the project you will work with different types of water, ranging from surface water to wastewater treatment plant effluent. The work will integrate hands-on monitoring with cutting edge data-driven and physical
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Learning Centre; A complete educational program for PhD students; Multiple courses on topics such as time management, handling stress and an online learning platform with 100+ different courses; 7 weeks
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large international consortium. Within the project you will work with different types of water, ranging from surface water to wastewater treatment plant effluent. The work will integrate hands
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analysis, AI algorithm modeling, testing, and integration into functional systems within the project scope. Specifically, in activities related to behavior modeling from IoT device data, generative AI
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specifically naval architecture, generative AI is lagging behind. This is largely due to data scarcity in the maritime domain. Unlike media domains where vast datasets are readily available, ship design data is
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coding the appropriate algorithms and methods that implement the novel concepts and model. Gathering experimental or observational data to test hypotheses or highlight the strength and boundaries
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specifically naval architecture, generative AI is lagging behind. This is largely due to data scarcity in the maritime domain. Unlike media domains where vast datasets are readily available, ship design data is