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-scale compound drivers. We will leverage machine learning methods to bridge the gap between drivers at coarse model resolutions and impacts captured by high-resolution observations. Job description Arctic
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the current work on independent continuous concepts to allow also for dependent and discrete concepts. The second project (“Weak supervision”) will instead focus on providing similar guarantees by integrating
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20 Feb 2026 Job Information Organisation/Company Eindhoven University of Technology (TU/e) Research Field Engineering » Computer engineering Engineering » Electronic engineering Researcher Profile
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of their PhD. With the aim of better aligning the Award with the needs in the field and current developments in the academic landscape, the Academy encourages the nomination of researchers for their contribution
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that can actively support the national electricity grid. Greenhouse companies currently provide a significant share of the Netherlands’ dispatchable power capacity; as they move away from fossil fuel based
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for complex dynamical systems to automate fault isolation with diagnostics performance guarantees. Current health monitoring technology is typically designed for either (i) individual system components/modules
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, exposing the limitations of current detection timelines. This reactive posture is worsened by a visibility gap in the DNS ecosystem. A lack of transparency in registration data, coupled with the short-lived
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. Methodological Approach Candidates will develop and apply state-of-the-art machine learning techniques, including deep learning, representation learning, variational autoencoders, and graph-based models. A strong
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. The current position entails conducting experimental research, publishing in peer-reviewed journals, presenting at conferences, and mentoring BSc and MSc students. The group values open interaction, knowledge
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, mathematicians, computer scientists, linguists, musicologists, and cognitive scientists, who share a fascination with the interdisciplinary study of information. This is what you will do Neural approaches