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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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Vitro Models. The project aims to use organ-on-a-chip technology combined with bioengineering approaches to develop, validate and use a suite of vascularised human tendon-chip models. These high quality
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Opportunities to produce high-quality publications Development of multidisciplinary skills in statistical modelling, machine learning, AF imaging and Raman spectroscopy and clinical translation of automated
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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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. Applicants should have a PhD in Cultural Geography, Environmental Arts or a closely related field; knowledge of current climate- and ocean-related scholarship in the Blue Humanities; a track record of
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-edge machine learning techniques will be used, including Large Language Models (LLMs). About Queen Mary At Queen Mary University of London, we believe that a diversity of ideas helps us achieve the
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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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of transposable elements and must be organised, highly self-motivated and have excellent communication and interpersonal skills. The post holder will be expected to prepare manuscripts using high-quality data and
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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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holder will join a multidisciplinary, diverse, and inclusive team with frequent meetings, interactions, and high-quality mentoring. About You You will have a PhD (or close to completion) in developmental