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and statistical methods as part of a close collaboration between Uppsala University, Westinghouse, and Vattenfall? Would you like to contribute to the development of fast, robust and reliable
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renewable energy use, energy security, and the reliable operation of hydro-dominated power systems. The project will focus on how AI can support advanced optimization models for hydropower and energy-system
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sits at the intersection of AI Safety and Data-Centric AI. We aim to make large-scale ML more reliable, transparent, and aligned with human values. We are specifically interested in: Data-centric AI
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: evaluating their behavior, improving their reliability for concrete use cases, and integrating them into systems with particular attention to security, explainability, and the interaction between humans and AI
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sits at the intersection of AI Safety and Data-Centric AI. We aim to make large-scale ML more reliable, transparent, and aligned with human values. We are specifically interested in: Data-centric AI
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beam (FIB) imaging - can be combined with AI to reconstruct nanoscale chip structures and infer functional behaviour from physical layouts. The project addresses the challenge of extracting reliable
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technologies. The goal of this project is to find a reliable packaging technique for silicon chips with embedded microfluidic channels that does not involve the use of glue or elastomer seals. The project will
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while retaining rigorous guarantees. The developed methods will be evaluated on benchmark problems and more realistic scenarios involving complex dynamical systems. You will join the Control Systems
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of extracting reliable structural and logical information from complex semiconductor architectures under realistic imaging constraints. Specifically, the researcher will focus on the following three main tasks:(a
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exactly that, working at the forefront of AI-driven ultrasonic evaluation of materials. Ultrasound plays a critical role in keeping our world safe and reliable. From inspecting aircraft components and