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of these materials and structures. This approach enhances both predictive simulation and inverse design strategies, optimizing the composition and arrangement of materials in the 3D design space. Within
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methods to improve systems, and ML research develops such methods. Major gains are made when the development of ML and systems are symbiotic and co-optimized. This is relevant across a broad spectrum of
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to produce restoration designs for multiple ecosystems’ at Utrecht University and the Royal Netherlands Institute for Sea Research, you will create ecosystem-specific, mass-produceable structures
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the creation and verification of pattern data files and tool-specific operation files for use on “direct write” systems; Develop and optimize new lithography processes (coating, exposure, development, inspection
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, boosted by AI-data augmentation for extrapolating spectrum patterns from multiple sources. To design a scalable computing framework using a physics-informed neural network for distributed spectrum analysis
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solution to support such a demand by getting inspired by the brain’s powerful and energy-efficient processing capabilities. MINDnet aims at addressing the challenge through a holistic optimization - from
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the brain’s powerful and energy-efficient processing capabilities. MINDnet aims at addressing the challenge through a holistic optimization - from individual computing devices to the overall architecture
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promising solution to support such a demand by getting inspired by the brain’s powerful and energy-efficient processing capabilities. MINDnet aims at addressing the challenge through a holistic optimization
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. MINDnet aims at addressing the challenge through a holistic optimization - from individual computing devices to the overall architecture, including a focus on applications, and training methods - across
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by getting inspired by the brain’s powerful and energy-efficient processing capabilities. MINDnet aims at addressing the challenge through a holistic optimization - from individual computing devices