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flexibility. To fully unlock this potential, we need advanced tools that digitally replicate these networks and support optimized design and data-driven control strategies. As our PhD candidate, you will
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a strong background in computational modeling, optimization, and systems engineering, eager to develop advanced design and simulation frameworks for battery pack topology and e-powertrain integration
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, market participation strategies and risk management, large-scale, distributed, multi-objective optimization techniques applied to energy markets and power systems and AI for optimization and control in
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, market participation strategies and risk management, large-scale, distributed, multi-objective optimization techniques applied to energy markets and power systems and AI for optimization and control in
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-scale, distributed, multi-objective optimization techniques applied to energy markets and power systems and AI for optimization and control in power and energy systems. The EES group has strong ties with
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-scale, distributed, multi-objective optimization techniques applied to energy markets and power systems and AI for optimization and control in power and energy systems. The EES group has strong ties with
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Are you fascinated by the large role software plays in the control of high-tech systems? Are you eager to contribute to improving supervisory controller development, and making it more structured
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in basic control-flow analysis. Process mining, as it stands today, is primarily based on computational techniques and algorithms to analyze and optimize processes. Methods such as process discovery
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chemistry, rheology, and curing dynamics control mechanical performance and print quality. Your role: Formulate novel ink systems with tailored polymer architectures and additives. Investigate how rheology
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of optimal control techniques. You have excellent verbal and written English language skills. As a university, we strive for equal opportunities for all, recognising that diversity takes many forms. We believe