12 postdoctoral-modelling Postdoctoral positions at University of London in United Kingdom
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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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About the Role We are looking for a motivated Postdoctoral Research Associate (PDRA) to join the research group of Professor Cédric John. You will be a key member of the John Lab, contributing
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including cell culture, organ-chip models, tissue engineering, and musculoskeletal biology. The PDRA will plan and conduct experiments, generate high-quality data, prepare publications, make presentations and
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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 Applications are invited for a Barts Charity-funded Postdoctoral Research Associate post to join the laboratory of Doctor Mathieu-Benoit Voisin within the Centre for Microvascular
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developed human discovery infrastructure enables recruitment of 200-300 severely injured patients annually as part of the ACIT study. We also have a well-established experimental modelling group with full
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About the Role – the project and research group Queen Mary University of London has a Postdoctoral Research Assistant vacancy to join the multidisciplinary project entitled “Human Tendon-CHIP: Novel
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Dr Heli Hietala. The postdoc project involves primarily simulations informed by observations, related data analysis and theory/models, comparing various aspects of shock particle acceleration and meso
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and Immigration website . Full-Time, Fixed-Term (18 months) Applications are invited for the post of Postdoctoral Research Associate in the Department of Mathematics for 18 months, starting 1st October
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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