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, contributing to our development and the success of our mission. The core responsibility of this role is the development of multiscale computational models, with particular emphasis on bio-based composite
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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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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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Grant “Advancing Gravitational-Wave Astronomy Using Artificial Intelligence” led by Dr Greg Ashton. The successful candidate will join Royal Holloway’s Astronomy Group and conduct research activities
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materials. Practical experience in fabricating 2D materials and a deep understanding of their structure-property relationships are highly desirable. You should also have expertise in advanced characterisation
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that demonstrates this effect on a laboratory scale, and that can be used to test the operando performance of various barocaloric materials and heat exchange structures. We are looking for a researcher to develop
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About the Role Applications are invited for one Postdoctoral Research Associate with expertise in structural biology to join the research group of Aravindan Ilangovan at Queen Mary University
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of computational and behavioural neuroscience with modelling and domestic chicks’ data. This position is funded by a Leverhulme Trust project entitled “Generalisation from limited experience: how to solve
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Research Council’s (AHRC) Bridging Responsibilities AI Divides (BRAID) programme that will explore new technologies, new business models and new approaches to data provenance in pursuit of an equitable
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the nature of celestial objects, the evolution of galaxies, and the structure of the Universe itself. We are also actively involved in the utilisation of upcoming facilities such as the Square Kilometre