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of fungal pathogens. The successful candidate will make extensive use of a range of in vivo models of fungal infection and will have access to the wide range of transgenic tools and in vivo immunology
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guidance to PhD students where appropriate to the discipline Contribute to developing new models, techniques and methods Undertake management/administration arising from research Contribute to Departmental
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and modeling of properties and spectra of PFAS chemicals with the goals of improving detection of PFAS compounds, replacing PFAS in plasma etching processes, or identifying solid adsorbent additives
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leveraged to accelerate learning from both classical and quantum data. The project will develop rigorous theoretical frameworks to understand key properties of quantum machine learning models—expressivity
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diffusion models using path integral formulations. This project aims to advance quantum machine learning by: Designing a quantum counterpart of diffusion models; Leveraging path integral methods to model
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developing new inverse modelling (‘retrieval’) methods to extract 3D information from JWST secondary eclipse observations. The models will be applied to JWST observations of giant transiting exoplanets
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Fixed Term Contract for 24 months We welcome applications from passionate and skilled post-PhD or experienced researchers in malacology, epidemiology, schistosomiasis modelling, or spatial data
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German Center for Diabetes Research (DZD) and the TransCampus collaboration with King's College London. We analyze large clinical cohorts and experimental models to unravel disease mechanisms and identify
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. Expertise in one or more of the following areas would be an advantage: Life cycle assessment, Life cycle social assessment, Techno-economic modelling, Materials flow analysis, Energy storage or battery supply
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extracellular histone, a damage-associated molecular pattern that is implicated in adverse outcomes after injury. This project will include using a range of clinically relevant models as well as in vitro