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validation in representative environments. The successful candidate will gain expertise in electrochemical sensing, microengineering, and computational modelling, and will join an interdisciplinary research
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predictive checking, model comparison) • Computational modelling with Python and Dynesty, JAX, NumPyro, and PyTorch • Use of asteroseismic and spectroscopic survey data (e.g. PLATO, Gaia, APOGEE, TESS) • High
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frameworks that can maximise the performance, efficiency, and emissions reduction potential of such new fuels through intelligent design, modelling, and experimental validation. Research Objectives Investigate
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Theoretical models for gravitational wave signals emitted by coalescing compact binaries are the cornerstone of modern gravitational wave astrophysics. Among the most pressing challenges
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Cardiometabolic diseases (CVMD), such as heart disease and type 2 diabetes, represent a major global health burden and exhibit stark ethnic disparities. Current clinical prediction models, even
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(ED&I) and alternative routes into research. Desirable skills include experience in modelling and simulation (MATLAB/Simulink, Python), energy systems, and intelligent control methods. Applicants should
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our ability to predictably control and exploit the drop for useful tasks. The proposed project has two aims: First, to develop computational models to quantitatively predict the response of chemically
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the corrosion of reinforcing steel, which compromises safety, durability, and sustainability. Current corrosion prediction models often fall short because they rely on oversimplified assumptions and
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integration into neural circuits to result in functional, restored behaviour. We will use the fruit-fly Drosophila as a model organism for its powerful genetics and molecular cell biology (e.g. CRISPR/Cas9 gene
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of realising an optical-pump TeraHertz-probe polarisation-resolved near-field microscope, this PhD research programme will look at combining spintronic THz emitters and near-field photoconductive probes