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control system that enhances Annual Energy Production (AEP), reduces mechanical stress, and improves fault detection using machine learning (ML) and physics-based modelling. The candidate will gain hands
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of Twente is looking for a highly motivated and talented PhD candidate to join our team. In this position, you will explore advanced frameworks to make complex interacting programs fault-tolerant and future
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, investigate error mitigation techniques Cooperate and actively work with international collaborators Your Profile: Master’s degree in physics, mathematics, or computer science Strong interest in both developing
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through accidental faults and targeted cyberattacks and how large scale constellations can achieve the same properties to protect for example, our energy grid. This position is initially funded for three
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of underwater acoustic environment or low signal-to-noise environment. We will develop more effective deep learning to increase data communication speed and reduce error probabilities. The project aims
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however require a significant measurement effort to be estimated, especially in the high-precision regime relevant for fault-tolerant quantum computing. You will investigate recent advances in
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. After initial experimental results, further research is guided by trial and error with the goal of deriving intuitive trends. Data-driven approaches are attractive alternatives. Descriptors are used
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results, further research is guided by trial and error with the goal of deriving intuitive trends. Data-driven approaches are attractive alternatives. Descriptors are used to characterize the molecular
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accurate reaction enthalpies and activation free energies for relevant intermediates. While quantum chemical predictions typically can provide sufficient accuracy of prediction (~1kcal/mol error