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the brain white matter. The network aims to strengthen the full translational pathway from disease mechanism and model development to preclinical therapy testing, clinical readiness and patient-informed
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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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materials characterisation and modelling. Techniques may include thermogravimetric analysis, in situ X-ray diffraction, SEM, EBSD, image analysis, thermodynamic calculations and kinetic modelling. The aim is
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and the various components of the tumour microenvironment. The research will primarily be conducted using patient-derived glioblastoma models and will combine approaches from cell and molecular biology
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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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Can you help unlock the data needed for the energy transition? In the NWO-funded SHARE project, you will develop AI models that generate realistic, privacy-preserving synthetic energy data for grid
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biogeochemical processes that govern their behaviour. Job description The PhD candidate will develop and analyse new process-based mathematical models to improve our understanding and predictive capability
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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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. To address this challenge, the project aims to develop structural health monitoring technologies based on a digital twin. The digital twin will combine information from the physical structure with models and
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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