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science and translational research models SHIELD supports research on therapeutic strategies, novel antimicrobial materials, and experimental models that bridge laboratory discoveries to clinical
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predictive accuracy and prohibitively long computational times, making them unsuitable for real-time process control. Artificial intelligence (AI) models present a promising alternative by addressing
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/or modelling is essential. Experience in machine learning, computer vision, and computer programming is desirable. In addition, applicants should be highly motivated, able to work independently, as
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essential to determine how these models can be made lightweight in terms of computational complexity, memory footprint, and energy consumption for deployment on edge devices or constrained gateways
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start dates: 1 October 2025 (Enrolment open from mid-September) Supervisors: Hari Arora (Biomedical Engineering), Richard Johnston (Materials) and Iain Whitaker (Medicine) Aligned programme of study: PhD
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of Strathclyde will lead the wind energy training and research elements of the programme. Funded by EPSRC, this 4 year PhD studentship, at the University of Strathclyde is in the area of novel wind turbine concept
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approach including empirical data analysis, experiments, and theoretical modelling to develop science-based management strategies for the restoration of woodland ecosystems. We will collect, and collate from
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models to predict defect behavior without the computational cost of DFT. The successful applicant should have or expect to achieve at least a 2.1 honours or equivalent at Bachelors or Masters level in
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-edge biological modelling to understand exactly how IIDs spread in nurseries. The project aims to develop improved intervention guidelines to prevent high mortality IIDs, considering what’s realistic and
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including predictive modelling, computer vision and epidemiology. The student will join an established team of investigators, including statisticians, epidemiologists, image scientists, and clinicians