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integrates machine learning and statistics to improve the efficiency and scalability of statistical algorithms. The project will develop innovative techniques to accelerate computational methods in uncertainty
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We are seeking a highly motivated candidate to undertake a PhD program titled "3D Temperature Field Reconstruction from Local Temperature Monitoring in Directed Energy Deposition." This exciting
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in our CDT program, and warmly encourage applications from students of all backgrounds, including those from underrepresented groups. We particularly welcome students with disabilities, neurodiverse
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. This project aims to dive into the dynamics of attack methodologies (e.g., Membership Inference, Property Inference) and defensive mechanisms (e.g., Differential Privacy, Machine Unlearning) within FL
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with intelligent technologies. These agents will enable the creation of dynamic, evolving services across various sectors, including healthcare, urban intelligence, and education, fostering continuous
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your academic profile in a friendly, supportive, and dynamic centre, with the possibility of contributing to scholarly and policy publications, research seminars and transitioning into a PhD and/or
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. The integration of AI into hardware not only enhances performance but also reduces energy consumption, addressing the growing demand for sustainable and efficient computing solutions. This PhD project delves
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, embedded intelligence, and adaptive cyber-physical systems that operate safely under uncertainty and dynamic conditions. This PhD at Cranfield University explores the development of resilient, AI-enabled
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candidate will conduct fundamental research aimed at understanding cell shape dynamics and the cross -talk between cell shape and cell state during epithelial-to-mesenchymal transition (EMT). The aim
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Applications are invited for a fully-funded 42-month PhD studentship with Dr Rachel Nicks and Prof Stephen Coombes on the Leverhulme Trust-funded project White Matter Computation: Utilising Axonal