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experiments, observations of natural earthquakes and numerical modelling to develop new insights into earthquake nucleation. The successful PDRA applicant will lead and contribute to laboratory experiments
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interpretable reduced-order models for fuel cell control using the Sparse Identification of Nonlinear Dynamics (SINDy) algorithm applied to numerical and experimental data. You will work closely with
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design. The role will combine experimental plasma science with numerical modelling to understand and improve nitrogen fixation pathways, alongside the use of analytical chemistry methods to quantify
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, homogenisation and numerics to develop, analyse and solve models of the coupled electrochemistry, mechanics and heat flow that determine the behaviour of batteries. The main focus of the research
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developing learning-based perceptive approaches. You will develop learning and/or optimization based approaches to multi-robot path and motion planning and coordination, integrating multi-modal perception and
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on the numerical and mathematical modelling of these complex atmospheric phenomena. This is a multifaceted research role that draws on mathematical modelling, high-fidelity numerical simulation, and close
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of natural earthquakes and numerical modelling to develop new insights into earthquake nucleation. The successful PDRA applicant will lead and contribute to laboratory experiments that investigate earthquake
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multiple ship classes and shore power applications. The project seeks to deliver industry-relevant modelling toolkits that enable optimal design and operation of greener vessels, backed by real-world
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at King’s on quantum algorithms and numerical methods for many-body dynamics beyond the reach of standard classical simulation. About the role We have a high preference for a candidates who is willing
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for implementing computational models, simulations, and numerical experiments is desirable. Diversity Committed to equality and valuing diversity Application Process You will be required to upload a covering letter