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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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research projects investigating novel strategies, discovered within our group, to combat heart failure. The work will integrate studies using isolated cell systems with advanced in vivo models, with a
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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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models and/or human samples Experience with eukaryotic cell culture systems Downloading a copy of our Job Description Full details of the role and the skills, knowledge and experience required can be found