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— on the materials modelling of ultrathin ferroelectric films. The overall goal of this research project is to produce strategies to manipulate the polarization in ultrathin ferroelectrics, and to design ferroelectric
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of (quantum and classical) integrability, one position emphasising the former and the other the latter. Some numerical skills is also expected. The post is offered at a competitive salary (spine points 31-35
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are passionate about applying machine learning to real-world clinical challenges. The successful candidate will lead the development and validation of predictive models using multimodal data including neuroimaging
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disease that affect neuromuscular systems and cortical circuitry, using human iPSC-based tissue culture models as their primary experimental system. The project will be co-supervised by Dr Ivo Lieberam
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R Holland, a preclinical research group with expertise in primary headache disorders, electrophysiology, disease modelling, behaviour, chemogenetics and in vivo neural imaging technologies
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within medical imaging and computational modelling technologies. Our objective is to facilitate research and teaching guided by clinical questions and is aimed at novelty, understanding of physiology and
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. The successful applicant will investigate the structure, dynamics, and motility of the bacterial Type IV pilus (T4P) machinery in the model organism Thermus thermophilus using theoretical modelling, simulation
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split 0.5FTE on the UKRI Medical Research Council funded project STARS: Sharing Tools and Artefacts for Reproducible Simulations in healthcare ; and 0.5FTE on the Health Service Modelling Associates (HSMA
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will conduct cutting-edge research at the intersection of neuroimaging, genomics, and computational modelling, with a focus on child and adolescent mental health. The successful candidate will primarily
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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 particular focus on characterising newly