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Field
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The role will develop new AI methods for identifying the instantaneous state of a fluid flow from partial sensor information. The research will couple techniques from optimization and control theory
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Department of Mechanical Engineering and the AI research group at the Vrije Universiteit Brussel (VUB) are looking for a PhD candidate to contribute to research on the optimization of a hybrid, laser-based
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and machine learning to tackle the complexity of force allocation and motion planning under uncertainty and actuator failures. The project combines theoretical research in stochastic optimal control
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dynamically managing power flow, improving system flexibility, and mitigating transmission constraints. However, conventional methods for PST deployment often consider sizing, placement, and control in
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garments into recycle, reuse, and manual-review streams; this PhD project tackles the core challenge of designing and optimizing a high-throughput hyperspectral imaging system, fused with complementary
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for Biomagnetism and Biosognalanalysis – ideally with you on board! The Project “Multi-channel transcranial current stimulation (mc-tCS): a novel approach to modulate smooth pursuit eye movement control in healthy
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of Electrical Engineering . You will be supervised by senior researchers with expertise in robotics, machine learning, automatic control, and optimization. The group leads and participates in numerous
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for growth and flux control. Engineering and optimization of microbial strains for production of bio-based products. Integration of metabolomics (targeted and untargeted), transcriptomics and proteomics
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techniques from optimization and control theory, scientific machine learning, and partial differential equations to create a new approach for data-driven analysis of fluid flows. The successful applicant will
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academic partners in Europe and globally. Candidates with the following qualifications will be preferred: Educational background in power systems. Documented knowledge in optimization in power and energy