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mouse models and immunology expertise (CRUK-CI), access to relevant patient material (matched fresh-frozen PDAC and serum samples). We will utilize AstraZeneca expertise in spatial and circulatory
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chromatin profiling methods along with CRISPR/Cas9-meduated cell line engineering and various animal models. You will study the effects of the activation or depletion of chromatin-modifying enzymes using
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This PhD project aims to develop and apply innovative photogrammetry-based analytical tools to enhance the spatial and structural characterisation of pharmaceutically relevant materials, with a
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. Project details In this project we aim to develop graph deep learning methods that model spatial-temporal brain dynamics for accurate and interpretable detection of neurodegenerative diseases
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framework exploiting the use of physical and geometrical conservation laws in a variety of spatial discretisation schemes (i.e. Finite Element, Finite Volume, Meshless). The resulting conservation-type
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sources such as (i) atmospheric models, (ii) satellite remote sensing, (iii) land use information, and (iv) meteorological data. The aim of this PhD is to develop and implement models for integrating data
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emerging types of national emergencies and evaluate their spatial and operational implications. This will include an analysis of UK population distributions, terrain, infrastructure access, and airspace
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search strategies 3) How to leverage the spatio-temporal diversity of multistatic radar observations At the end of the PhD an over-arching modelling environment will be built, where the parameters above
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Application deadline: 01/08/2025 Research theme: Turbulence, Fluid Mechanics, Offshore Conditions, Renewable Energy, Hydrodynamics, Experiments This 3.5 year PhD is fully funded for applicants from
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. Experimental studies will be performed in wind tunnels with advanced measurement techniques with high spatial and temporal resolutions. Realistic car models (DrivAer models) will be considered in this study and