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–specific ways, and their downstream biological effects remain poorly understood. This project tackles this fundamental gap — by building computational models that simulate what goes wrong in the brain, one
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handling, enabling first-time-right manufacturing. The predictive quality of these tools relies on accurate constitutive models that describe the behavior of the molten material during forming. With
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development, modelling, and system-level optimization in one of Europe’s most vibrant research ecosystems for sustainable energy and transport.
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into the psychological factors that impair consumers' ability to detect such deceptive claims. The project will develop and test a Washing Detection Model to better understand when and why consumers are vulnerable
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adaptation, and livelihood systems model. This PhD vacancy is linked with WP4 on water, sanitation and hygiene (WASH) services and public health. This is an interdisciplinary project embedded within a vibrant
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Manufacturing (AM) is increasingly applied in repair and remanufacturing; however, integrating AM into supply chains demands new models and methods. In this PhD project, you will: develop dynamic supply chain
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and consequences of localized translation, following up on our recent work (Ramalho et al, 2025, Sci Adv). You will combine ribosome profiling and organoid models with molecular and computational
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design of multi-armed bandits and reinforcement learning models with applications to recommendation systems and clinical trials (Gui Liberali), privacy (Gilian Ponte), causal inference (Jason Roos
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innovation management involves all actions needed to generate creative ideas and to turn these into attractive new products, services, and business models. The Innovation Management group at RSM is a team
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introduced into the PhD trajectory and scientific working. You will alongside the developers of UT’s global crop water model ACEA (Mialyk et al. 2024) and improve the model’s ability to provide recurring