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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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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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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
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vitro, organoid co-culture models will be developed using primary human epithelial cells. Candidates should have an excellent research track record, be committed to the project and keen to work in a
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, advanced imaging techniques and numerical modelling. About the role A successful candidate will be working on the EPSRC funded project New perspectives in photocatalysis and near-surface chemistry: catalysis
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expertise in organoid models of neurodevelopment to join our team and be involved in a MRC funded project aimed at generating region-specific brain organoids and assembloids from multiple gene-edited human
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of liver micrometastases development in cancer, based on a novel MRI approach which combines multi-dimensional diffusion-relaxometry acquisitions, efficient data denoising and biophysical modelling
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schizophrenia-related symptoms in animal models (mice), in the context of a collaborative project with clinicians and computational scientists. This project will be supervised by Prof Oscar Marin and Prof Beatriz
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of liver micrometastases development in cancer, based on a novel MRI approach which combines multi-dimensional diffusion-relaxometry acquisitions, efficient data denoising and biophysical modelling
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within macrophages – key cells of the innate immune system. The Hill Group uses Salmonella enterica serovar Typhimurium as a model pathogen to investigate how host–pathogen interactions contribute