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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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Multiphysics software (COMSOL and/or Abaqus), python/matlab coding and Molecular Dynamics Simulator (LAMMPs). 4. Publications in mechanical metamaterials, soft robotics, or related area in peer-reviewed
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networks. The research will employ mathematical modelling and computer simulation to identify synaptic plasticity rules which enable effective learning in large and deep networks and is consistent with
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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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, spatial, and social data into digital twin models for scenario testing and policy simulation. Adapt co-design methods to local contexts in demonstrator sites (Portugal, Sweden, Italy). Contribute to policy
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and/or flow cytometry-based readouts of infection Experience with biochemical assays (e.g. Western blotting) Experience handling/processing samples in vivo infection models and/or human samples
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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
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vitro and in vivo infection models, and both microscopy and flow cytometry-based readouts of infection to develop their independent research project and will also be expected to collaborate more widely