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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
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to increase resource use efficiency. However, managing and optimizing these new cultivation systems requires crop models that can predict plant growth, crop yield and resource use under highly dynamic
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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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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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process. This project offers a unique opportunity to work at the intersection of machine learning and control theory. You will develop rigorous theory and scalable computational methods for certifying
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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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: 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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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
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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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through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Are you fascinated by the idea