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Field
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Description The field of combinatorial optimization is concerned with developing generic tools that take a declarative problem description andautomatically compute an optimal solution to it. Often, users
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renewable energy generation.KU Leuven leads Modelling and Optimization, which focuses on: Developing hybrid models combining first-principle and machine learning approaches. Creating predictive frameworks
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optimized designs in actual resonant power converters using WBG semiconductors. The expected outcomes include a robust 3-D modelling framework, novel low-leakage magnetic layouts, and an advanced design
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, and heterogeneity of 6G networks, for their analysis and optimization, we use tools such as artificial intelligence/machine learning, quantum conputing, graph theory, graph-signal processing, and
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networks, for their analysis and optimization, we use tools such as artificial intelligence/machine learning, graph theory and graph-signal processing, and convex/non-convex optimization. Furthermore, our
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include nucleic acid extractions, Sanger sequencing, PCR assay optimization and RT-qPCR. This position offers the opportunity to work closely with a dynamic team of PhD students and postdoctoral researchers
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and the characterization of their pigments, through the optimization of their production and application, to the comprehensive ecological and economic evaluation of the resulting solutions
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proactive decision-making. Good understanding of mathematical optimization techniques for resource allocation and multi-objective trade-offs. Background knowledge in mobile and satellite networks, network
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on developing data-driven, low-order aerodynamic models of VPPs, updated in real time with experimental data, and using them to design control strategies for flight stability and performance optimization
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Optimization: Define and implement process splits in collaboration with characterization and process step engineers. Analyze interactions between FEOL modules and guide development based on electrical and