17 modelling-complexity-geocomputation Postdoctoral positions at University of London
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About the Role A Postdoctoral Research Assistant (PDRA) is sought to join the musculoskeletal organ-chip research team within Queen Mary’s Centre for Predictive in vitro Models. This 23-month post
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project is to develop a series of surrogate models focusing notably on Physics-Informed Neural Networks to emulate the process of sediment deposition, diagenesis, and potentially fracturing, working closely
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migration and in vivo murine models of inflammation and technical expertise in complex flow cytometry is essential. The previous ability to work with rodents would be advantageous, whilst experience in
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potential applications in audio and music processing. Standard neural network training practices largely follow an open-loop paradigm, where the evolving state of the model typically does not influence
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interdisciplinary team of researchers. You will have excellent communication skills, and the ability to explain complex ideas to a variety of different stakeholders, including policy makers. About the Project You
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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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In Vitro Predictive Models to Explore Tendinopathy”. The project is funded by the Medical Research Council (MRC) and part of the organ-chip research work underway within the Centre for Predictive in
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to work on a project investigating mechanosensing in flies (Diptera). This post will focus on using detailed wing geometry models and free flight kinematic measurements in computational fluid and structural
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disease progression. About You Applicants should hold a PhD degree or equivalent in biological or related science and have a strong background in immune cell biology and animal models of inflammatory and/or
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support projects using GWAS, Mendelian Randomisation, and polygenic risk score analysis to uncover genetic mechanisms underlying complex traits. There are opportunities to integrate omics data across