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their scales, exploring parameter space for vortex behaviour using theory and idealised model simulations, testing the relevance of the new paradigm using case studies observed using during the NERC
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, economics, environmental science). You will bring expertise in food systems modelling, supported by a strong technical background that may span areas such as data science, input–output analysis, applied
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. The successful applicant will investigate the structure, dynamics, and motility of the bacterial Type IV pilus (T4P) machinery in the model organism Thermus thermophilus using theoretical modelling, simulation
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About the Role This is an opportunity to work as part of the team and project “Development of Multi-Modal Foundational Models and AI Accelerators for Zero-shot Intelligent Surveillance System
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experience in: Deep learning Medical imaging computing (preferably neuroimaging) Computationally efficient deep learning Deep learning model generalisation techniques. Translating deep learning models
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for carrying out research to develop iPSC-derived lung cell models. Working within a team of biochemists, cell and structural biologists, you will perform experimental work to apply omics technologies, advanced
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navigation algorithms and machine learning models on physical robot platforms. We are particularly interested in candidates with expertise in generative AI and curriculum learning applied to robotics, as
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megakaryocyte cell communication and coordination. We will employ a range of approaches including advanced microscopy (confocal and intravital), models of thrombus formation (ex vivo and in vivo ), and flow
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plumes. Emissions plumes from high-altitude sources (e.g. aircraft) can persist for weeks or even months in the stratosphere, but most global atmospheric models are unable to preserve such fine structure
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humanised mouse models with the same mutations as patients, all of which are currently available in the laboratory. Minimum qualifications are PhD and/or MD with expertise in molecular and cellular biology