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. The studentship will start on 1st October 2026. Project Description Project Aim To develop and validate an AI co-pilot software system integrating multi-modal radiomics data to enhance cancer detection speed and
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vegetation-enhanced performance will have significant application. Working in the University’s world class COAST Laboratory, you will develop and validate physical modelling techniques to represent vegetation
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develop physics‑informed neural surrogates to support real‑time digital‑twin CFD for offshore wind turbines. Key objectives include: Designing PINN and operator‑learning models that enforce incompressible
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Ryzen CPU, GPU, and NPU, in terms of inference speed, energy consumption, accuracy, and performance per watt. Different quantization levels (e.g., int8, fp16) will also be explored. Develop intelligent
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EPSRC funded UDLA PhD studentship. The studentship will start on 1st October 2026. Project Description The project aim is to develop novel FETs and biosensors based on Graphene and 2D Materials
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will develop new mathematical tools to analyse brain imaging data using persistent homology, a method from topological data analysis (TDA) that captures the shape and connectivity of complex data across
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for diagnosis and prediction of disease progression. The project will provide opportunity to: Be involved in a research project with direct clinical impact Develop expertise in VR based vision assessment Develop
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with leading industry partners in wearable medical devices such as SONA, gaining insight into commercial healthcare technologies. Overall, this PhD provides an exceptional platform to develop both