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will work at numerous sites across the UK, including in East Anglia, Somerset, and Lancashire. The position will involve extensive fieldwork duties, frequently with overnight stays, and you should be
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with these collaborators. The research will involve both analytical work and numerical computations. The balance between analytical and numerical type work is flexible and can depend on the preferences
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of fluids and soft solids. • Ability to design theoretical models and carry out appropriate analytical calculations to achieve the proposed objectives. • Experience in numerical
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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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project investigating mechanosensing in Diptera. This post will focus on using detailed wing geometry models and kinematic measurements in computational fluid and structural dynamics simulations to recover
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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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expertise in analysing/ training models on biological or chemical datasets Proficiency in Python for data science and machine learning Possess sufficient breadth or depth of specialist knowledge with deep
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. We are a highly international and research-oriented Department. More than 30 full-time junior and senior professors together with numerous PhD students form an international community dedicated
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About the Role The combination of personalised biophysical models and deep learning techniques with a digital twin approach has the potential to generate new treatments for cardiac diseases. Our
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About the Role The combination of personalised biophysical models and deep learning techniques with a digital twin approach has the potential to generate new treatments for cardiac diseases. Our