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for data-efficient vision foundation models. Foundation models in computer vision currently rely on massive datasets and brute-force scaling. This leads to high data requirements, hidden biases, limited
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for the next generation of commercial aircraft, combining excellent mechanical performance with low weight. In addition, their melt-processable matrix enables automated, high-rate manufacturing of components
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acceptance remains limited due to insufficient meat aroma and persistent off-flavors. PBMAs are typically produced by texturizing plant proteins through extrusion or shear cell processing, both of which
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? The NWA-ORC funded consortium project ABEL addresses this challenge by combining technology development with process modelling and assessment across the waste value chain. The members of the consortium
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-inspired computing paradigm with the potential to drastically reduce energy consumption while enabling faster inference than conventional digital architectures. A major challenge, however, is the development
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requires detailed imaging, beyond what is currently possible in humans in vivo. In an NWO-funded Vici project, we leverage Ultra-High Field MRI to bring the cerebellar mesoscale into view. In this PhD
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accurate despite the large temperature gradients present in cryogenic experiments. You will explore full-field techniques such as digital image correlation, speckle and grid methods, interferometry, digital
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business, while obtaining your PHD. A key aspect of this position is your curiosity and ability to explore and apply applied research in a practical context. You continuously investigate emerging digital
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characterization, o microscopy and metallurgy, o (micro-)mechanical testing, in-situ testing and digital image correlation, o numerical analysis of experimental data. We look forward to receiving your application
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– AI-generated text, audio, images, and video. However, given their still developing cognitive skills, they may also be least equipped to deal with synthetic content. This project investigates how