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of asphalt mixtures exposed to climate-induced stresses such as temperature fluctuations, moisture variations, and UV radiation. The study will involve both laboratory experiments and numerical modelling
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are looking for a PhD candidate to research new adaptative architectures and foundation models for the integration of healthcare data specifically incorporating patient preferences. This includes challenges
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environments. The researcher will work on modelling relevant propagation effects, designing localization strategies robust to urban acoustics, and validating these techniques using state-of-the-art experimental
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OCT system must be optimized in terms of noise and detection efficiency. You will do this based on experiments and physical modeling of SC, detector, and system performance. Second, the OCT system must
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involving Fluid Dynamics. Demonstrable affinity with studying the physics of the ocean and preferably with polar oceanography. Experience with numerical modelling. Excellent ability to communicate in both
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specifically, do you want to perform cutting-edge research and develop novel advances in hyperbolic deep learning for computer vision? Then check out the vacancy below and apply for a PhD position in this
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architecture, preferably with a focus on structures. Know the basics of (structural) glass and of Dutch masonry (heritage) buildings. Have a solid understanding of computational/numerical modelling and
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work on the following: Design of an efficient foundation model (FM) for generalization across patient anatomies, pathologies, and coil arrangements to infer optimal sensor settings from partial data
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-cities in Asia and Africa, and suggest (if possible) solutions to ameliorate bad air quality during the fire season. You will combine the Dutch air-quality model LOTOS-EUROS with satellite observations, in
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where trustworthiness is essential. Today’s explainability methods often do not provide meaningful decision support and, in some cases, can even leak sensitive training data. Models are especially