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Field
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at the intersection of theory, computation, and high‑fidelity simulation, the successful candidate will contribute to the development of a novel ensemble-based framework for analysing driven perturbations in wall
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The rapid growth of deep learning has come at an extraordinary environmental and computational cost, yet the standard training paradigm remains remarkably unchanged. Every sample is passed through
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we are looking for The candidate should have a 1st or high 2:1 degree in mechanical/aerospace/manufacturing engineering, computer science, physics, mathematics, or related scientific disciplines
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This studentship is fully-funded by an EPSRC Industrial Doctoral Landscape Award in partnership with AWE plc. The successful applicant will be welcomed into our world-leading research programme
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, implementation, and evaluation of trials and interventions through the Adolescent Interventions for Mental Health in Bradford (AIM Bradford) programme (www.aimbradford.nhs.uk). This project is ideal for candidates
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training will be provided by the supervisors and lead stakeholder partner in fieldwork methods, research impact and policy engagement. Funding The successful applicant will receive a full PhD scholarship for
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of the Ministry of Defence whose goal is to maximise the impact of science and technology for the defence and security of the UK. The project will involve working in collaboration with expert DSTL scientists, with
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, computer science, or a closely related discipline (typically first-class or high 2:1, or equivalent; Master’s welcome) • Strong programming skills (for example Python, MATLAB, C/C++) • Strength in at least two of
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Semiconductors are key enablers of virtually every aspect of modern society from smart phones and computers to energy generation, communications, AI, defence, transport and healthcare. Without
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in recombination under heat stress. In this PhD project, the student will investigate how temperature affects crossover patterning in plants and test whether shifts in HEI10 dynamics can explain