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smart industry. You will be part of a large national ‘Perspectief’ program Foundation Models for Industry (FIND), collaborating with leading Dutch universities, knowledge institutes, and industry partners
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of Contract Temporary Job Status Not Applicable Hours Per Week 38.0 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a
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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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on the development of new platforms for osteoarthritis research, including advanced in vitro and ex vivo culture models. With these models we strive to reduce and replace animal experiments while working towards
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on accurate constitutive models that describe the behavior of the molten material during forming. With the increasing demand for more complex components, a step change in model accuracy and associated material
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from, collaborate with, support, or improve humans; Deep Learning for Perception: Use of deep learning algorithms for computer vision, image and audio processing, and models of perception. The focus is
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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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Application Deadline 1 Dec 2025 - 22:59 (UTC) Type of Contract Temporary Job Status Not Applicable Hours Per Week 40.0 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme
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-driven model for assessing the reliability of official network maps (KLIC deliveries). You will build a prototype algorithm that can be used by infrastructure and civil engineering professionals to better
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to have the following skills and experience. We welcome applications from individuals with experience in: Deep learning Medical image computing (preferably x-ray imaging) Computationally efficient deep