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-based workshops; and System Dynamics Modelling, to understand how to maximise the contribution of Nature Based Solutions to climate change adaptation in the UK through multifunctional landscapes in
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learning “emulators” of multiple ice sheet and glacier models, based on large ensembles of simulations extending to 2300. The simulations will be from two international projects aiming to inform
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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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and experience: Essential criteria PhD in bioinformatics, computational biology, or a related discipline * Extensive experience and expertise in analysing/ training models on biological or chemical
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About us The Green Laboratory investigates tissue morphogenesis and the action of morphogens. We use animal models to investigate the physical morphogenesis of tissues. It is part of the vibrant and
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the regulation of capsule expression during transition between host compartments. The successful candidate will combine cutting-edge in vitro and in vivo infection models, and both microscopy and flow cytometry
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structural development over time at the group, sub-group, and individual level (e.g., using normative modelling and clustering approaches to parse heterogeneity). The candidates will further have the
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of the microbiome in olfaction using mouse models. The selected applicant will join the vibrant and friendly Tucker lab and work as part of a team interacting with the group of Prof Mike Curtis. The postdoc will
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, alongside strong skills in protein analysis, molecular biology, and imaging techniques. Additional expertise in studying autophagy and using preclinical mouse models of cardiovascular disease are highly
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of background knowledge; implicit knowledge is derived by performing reasoning over event graphs; and the comprehension model is developed with built-in interpretability and robustness against adversarial attacks