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Field
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, yielding solutions that are less sensitive to perturbations and therefore more reliable in practice. Mathematically, this leads to optimization problems with underlying random partial or ordinary
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on facility location, storage, processing capacity, procurement, and inventory management. The project combines: stochastic and robust optimization, uncertainty modelling, large-scale supply chain design, and
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: - A PhD degree in optimization or systems and control theory. - A strong mathematical background and an interest in conducting theoretical research. - A proven track record. - Excellent English
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perform desktop studies related to process design and optimization, techno-economic evaluations, and screening of purification technologies. What are you going to do? The main objective of this EngD project
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critical for achieving power-efficient operation, programmability, high linearity and low-noise signal conditioning including optimal dynamic range and bandwidth utilization. This position offers a unique
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largely by the rapid expansion of artificial intelligence (AI), cloud computing, and high-performance data processing applications. As AI models continue to increase in size and computational complexity
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the effects of optimized gene expression regulation on plant performance under optimal and field-like conditions at the Netherlands Plant Eco-phenotyping Centre. Your research aims to improve tomato Zn and Fe
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twins, optimization, and control. In this PhD project, you will develop a new systems and control theory for learned operators, bridging modern scientific machine learning with classical control theory
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not sufficiently understood. In particular, the interplay between surface properties, wafer morphology, and the resulting bonding performance is still largely optimized empirically. In this postdoctoral
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work on plant genetics, growth strategies, and crop management with the aim of achieving optimal crop performance by integrating plant, environment, and management. The position offers close