47 modelling-and-simulation-of-combustion-postdoc Postdoctoral positions at KINGS COLLEGE LONDON
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are entitled to at least 10 days per year (pro-rata) for professional development. This entitlement, from the Concordat to Support the Career Development of Researchers, applies to Postdocs, Research Assistants
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to Postdocs, Research Assistants, Research and Teaching Technicians, Teaching Fellows and AEP equivalent up to and including grade 7. Visit the Centre for Research Staff Development for more information
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to Postdocs, Research Assistants, Research and Teaching Technicians, Teaching Fellows and AEP equivalent up to and including grade 7. Visit the Centre for Research Staff Development for more information. About
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, develop risk models, and help generate new hypotheses to inform future therapeutic strategies. The role offers a unique opportunity to bridge data-driven insight with translational cardiovascular research
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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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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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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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collaboration with Prof. Giovanna Tinetti and her team and collaborators at KCL. The main purpose of this role is to develop new and/or to use existing models to simulate the atmospheres of exoplanets and use
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Clear interest in and knowledge of current understanding of vertebrate development Knowledge of use of chick as a model system Knowledge of limb development and evolution Downloading a copy of our Job
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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