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to design an AI system that integrates scientific knowledge for early dementia modelling, based on large language models and causal inference. The project has two stages: first, to construct a causal
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preclinical evaluation in physiologically relevant 3D models. This PhD position sits at the interface of nanochemistry, and translational cancer research, and offers the opportunity to contribute to a next
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phenotyping, microbiome profiling, predictive modelling and targeted experimental validation to identify the microbial factors that make plants more resilient to disease. Your job You will join the Plant
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-learning models that connect powder characteristics and process parameters with the properties of the final components. These models will support faster feedstock qualification and enable predictive quality
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to the development of state-of-the-art nuclear-reaction models and evaluated nuclear-data libraries, supporting safe, reliable, and competitive technologies for both existing and future nuclear-energy systems, as
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are developing a suite of models to deliver a through-process microstructural and mechanical property prediction framework for steel. By integrating these models into a cohesive digital twin architecture, the work
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white matter. The network aims to strengthen the full translational pathway, from understanding disease mechanisms and developing disease models to preclinical therapy testing, clinical readiness and
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to staff position within a Research Infrastructure? No Offer Description The project explores extreme light–matter interactions at the nanoscale, developing advanced theoretical models in direct
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(further funding will be applied for) and focuses on power systems engineering in the context of the next phase of Iceland’s energy transition. It builds directly on established modeling work at Reykjavík
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Some of the biggest open questions in modern physics concern the limits of the Standard Model and General Relativity. The nature of dark matter and dark energy remains unknown, and many theories