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Field
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The overarching aim of the project is to understand how early neurodevelopmental risk factors disrupt brain maturation and contribute to psychosis vulnerability across development. This PhD project
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Research Studentship in ‘Deformation and fracture of TRISO fuel particles’ 3.5-year DPhil studentship Supervisor: Prof Dong Liu, Prof Emilio Martinez-Paneda About the Project The proposed PhD
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reinforcement learning, LLMs can iteratively improve by learning from feedback. If successful, this approach could present a ground-breaking solution for system software development. The candidate in this role
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The project will work alongside Vishay Intertechnology, which brings together a number of world leaders in power semiconductors and energy conversion to develop solutions for automotive, aerospace, industrial and grid-level power electronics. The purpose is to improve the electric vehicles and...
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The Child and adolescent Health Impacts of Learning Indoor environments under net zero (CHILI) Hub is a program funded by the MRC and NIHR, the goal of which is to understand the health effects we
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Supervised by: Rasa Remenyte-Prescott (Faculty of Engineering, Resilience Engineering Research Group) Aim: Develop a mathematical model for obsolescence modelling for railway signalling and telecoms Background Network Rail operates several telecom networks which provide connectivity for various...
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for research into thermal management and system health monitoring, supporting studies in military aircraft systems. Engaging with these facilities allows students to acquire practical skills and technical
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science, along with proven skills in prototyping software using real-time 3D engines and implementing machine learning models. With 50+ researchers and PhD students, the Centre for Sustainable Cyber Security (CS2
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This exciting fully funded PhD, with an enhanced stipend of £25,726 per annum (with fees covered), will deliver a comprehensive understanding of micropollutant removal in different types of nature
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which there exists extensive experience in the areas of machine learning, biostatistics, and medicine: Dr Yanda Meng and Dr Tianjin Huang (Machine Learning), Prof Yalin Zheng (AI in Healthcare), A/Prof