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, demand uncertainty, and storage limitations. Quantify uncertainty: Apply advanced techniques to assess and mitigate market-driven performance and investment risks. Develop real-time control schemes: Design
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architectures, and on-device inference on edge-compute platforms. Demonstrated analytical problem-solving through experimental design, critical quantitative and qualitative data analysis, and validation
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testing, to achieve sub-second cycle times for robotic systems. 3. Demonstrated analytical problem-solving through experimental design, critical quantitative and qualitative data analysis, and validation
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the computational imaging group at CWI, where you will have a chance to interact and collaborate with fellow PhD-students and research staff with a background in mathematics, computer science, and imaging science. It
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over 600 known members. These compounds pose a significant risk to food safety, yet their full characterization remains a major analytical challenge due to their chemical complexity and natural
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the analysis. These logistics concepts must be resilient: robust, adaptive, and flexible. The research questions can be tackled by combining techniques from the domains of Integer programming, (Stochastic
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-waiting – were successful spies in seventeenth-century England. This is what Nadine Akkerman describes in her book Invisible Agents, the first analysis of the role of female spies in the seventeenth century