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Field
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Faculty of Engineering and Physical Sciences EPSRC Project Proposals 2026/27 (jobs.ac.uk) Project Link via the 'Apply' button above Project Title: Machine Learning Driven Corrosion Modelling in Bio
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the latest data from climate models which contain information for how the climate, the population and its vulnerability/exposure are projected to change under various socio-economic scenarios. The information
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research into predictive failure analysis methodologies for HVDC interconnection systems. This will include assessments of primary components such as switchgear and power transformers, as well as essential
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induced seismicity. Current models remain limited by the scarcity, heterogeneity, and noise of available data, as well as by incomplete knowledge of the subsurface. Physics-Informed Neural Networks (PINNs
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, radiologists interpret scans such as CT, MRI, and X-ray together with textual information, including patient history, laboratory findings, and prior reports. Although recent Vision–Language Models (VLMs) can
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underexplored. Rather than functioning as neutral tools, algorithmic models translate complex realities into scores, rankings, classifications, and predictions. In doing so, they shape how problems are defined
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predictive models, and interpreting large environmental datasets, collaborating in interdisciplinary projects and in the production of scientific publications. In the performance of duties, it may sometimes be
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of pathogens, their interactions with hosts and the environment, and how they are transmitted through populations. Research will have a strong focus on computational analysis or predictive modelling of pathogen
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for three years. The project focuses on environmental sustainability in grain storage, developing telemetric robotic sensing and predictive modelling to control mycotoxin (Ochratoxin A) risk while reducing
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the challenge of forever chemicals in drinking water. The aim of this research is to develop a smart data predictive model that will support utilities’ evidence-based decision-making to improve the resilience and