577 phd-studenship-in-computer-vision-and-machine-learning PhD positions in United Kingdom
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Electrical and Electronic Engineering Department, Imperial College London PhD Studentship in Damping of IBR-induced Oscillation Position Summary: Applications are invited for a PhD studentship, to
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treatment processes through advanced machine learning, validated against physics-based models and experimental data. System Integration: Integrating the DTs into material and energy balance equations
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This 4-year PhD project is open to home student and fully funded; the successful candidate will receive a tax-free stipend based on the UKRI rate (£20,780 for 2025-25) and tuition fees will be paid
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into car cabins (to reduce the exposure of occupants) and the regions where pollutants accumulate (to be avoided by pedestrians and cyclists) need to be minimised. The PhD objective is to study the effects
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the foundation of computer vision, monitoring, and control solutions. However, real applications of AI have typically been demonstrated under highly controlled conditions. Battery assembly processes can be
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Deadline: 30 September 2025 A fully funded 3.5 year PhD position is available to work on the project titled “Scalable benchmarking for digital quantum computers based on blind testing
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PhD studentship: Defining the role of the pioneer factor FOXA1 in hormone-dependent cancer Supervisor: Professor Jason Carroll Course start date: 1st October 2026 Project details For further
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Supervisory Team: Leonardo Aniello, Han Wu PhD Supervisor: Leonardo Aniello Project description: Blockchain and Federated Learning (FL) are two emerging technologies that, when combined, offer a
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members of staff. Research in the Department is organised into six themes : Causality; Computational Statistics and Machine Learning; Economics, Finance and Business; Environmental Statistics; Probability
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sustainability goals whilst improving operational efficiency? This PhD studentship will involve developing machine learning models, creating virtual manufacturing replicas, and implementing optimisation algorithms