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the spatial reasoning capabilities of multi-mode large language models and hybrid AI systems combining artificial neural networks with symbolic AI. In-house research and development of one of these systems
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. As part of BioM , the candidate will work in an interdisciplinary team of biologists, statisticians and philosophers, including one other PhD student (statistics) and two postdocs (spatial forest
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, antigen presentation and trained immunity) using mouse models that enable CPT1A gain or loss of function. Furthermore, the bioenergetic profile of macrophages both in vitro and ex vivo will be assessed
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will be working in an experimental lab, performing data collection, analysis, and modeling of behavioral and electrophysiological data. Applications are invited to apply for a statistical data analysis
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exhibit hallmarks of active matter. This PhD project aims to develop theoretical and computational active-matter models of early mouse embryogenesis that couple collective cell mechanics with gene
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well as in liver regeneration and cancer. Leveraging publicly available spatial datasets, this project aims to develop data-informed computational modelling and systems biology framework to dissect molecular
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, intensity) in the vicinity of sound sources, providing a precise spatial and frequency-domain representation of acoustic radiation. Introduced by Williams [1], acoustic holography has gained widespread
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zebrafish embryos as a model organism with the ambitious aim of establishing clear evidence for extracellular vesicle-driven crosstalk in the brain beyond synapses. Through the project, you will be trained as
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Results: Ability to assess the influence of the engine plume on the release of emissions into different atmospheric layers. Numerical model to describe the temporal and spatial dispersion behaviour
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African ocean basins. O2. Building anticipatory governance to ensure that actions to achieve transformative visions are sensitive to multi-scale temporal and spatial dynamics. SRC is leading WP 2 that aims