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systems, or continuous-time and discrete-time LTI systems theory is a plus. Experience with mathematical modeling, optimization, numerical computation, algorithm development, or machine learning. Prior
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for three consecutive periods (2014-2018 and 2018-2022 and 2023-2026). ICN2 comprises 20 Research Groups, 7 Technical Development and Support Units and Facilities, and 2 Research Platforms, covering different
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renewable energy use, energy security, and the reliable operation of hydro-dominated power systems. The project will focus on how AI can support advanced optimization models for hydropower and energy-system
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-time operation. The project will focus on how AI and mathematical optimization can be combined to support sequential bidding decisions under uncertainty. The initial use case will consider a wind power
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its inverse reconstruction. A key challenge is the data-driven design of the experimental setup: exploring how the choice of measurements and configurations can be optimized to extract the most useful
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with a strong background in applied mathematics, control theory and/or optimization to apply for a fully funded 4-year PhD position in the Smart Manufacturing Systems (SMS) group at the Engineering and
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tissue exposure, and the systematic investigation of different treatment scenarios should finally allow deriving optimized treatment strategies within PRESTO which can be used in treatment planning. Your
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methodologies for assessing Local Energy Communities. Contribute to the integration of market and economic considerations into mathematical optimization models. Analyze electricity market structures, pricing
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retrieve shapes, overlay errors, and other geometrical parameters of the target using methods ranging from local and global optimizers to priors and neural networks developed by partners in the project. Job
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and prior knowledge of the sample geometry. You investigate and optimize the trade-off between accuracy and imaging speed. For real-time application, the speed and accuracy of the algorithms will be