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. The state-of-the-art approaches in optimal climate control of greenhouses are based on implementing economic objective functions exploiting a time scale decomposition between short-term climate control/energy
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selection and validation, supervised and unsupervised learning, optimization techniques, (deep) neural networks, probabilistic methods and statistics, data visualization, natural language processing
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, and optimization. This research is reinforced by close collaborations with industry. You will receive close scientific supervision while having the freedom to shape your research direction, present your
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confidence in the measurements and establish traceable validation routes. Optimize the methods for realistic converter operating conditions and communicate practical guidance to academic and industrial users
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: designing, performing and interpreting experiments for simultaneous texturization and flavor generation in PBMAs; contributing to the development and optimization of analytical methods; publishing your
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Challenge: Extreme water events threaten people and infrastructure Change: Understand impact dynamics with experiments and numerical simulations Impact: Optimize the design of resilient
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Utrecht, CWI, Dutch municipalities, DSOs, and other societal/industry partners. The project brings together expertise in energy informatics, optimization, data science, social sciences, and governance
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Computational de novo design of VHH and scFv binders to blood coagulation factors such as factor Xa and prothrombin. Wet lab production and screening of the aforementioned binders. Optimization
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cardiovascular medicine. Mechanical Circulatory Support (MCS) technologies offer life-saving potential, yet optimal patient selection, timing, and device strategies require deeper mechanistic and clinical insight
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at cryogenic conditions: Many advanced technologies — like quantum computers, powerful microscopes, and chip-making tools — require extreme cooling. However, the optimal design of cooling systems at cryogenic