756 phd-studenship-in-computer-vision-and-machine-learning PhD positions in United Kingdom
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thermodynamically. Performance design optimization and advanced performance simulation methods will be investigated, and corresponding computer software will be developed. The research will contribute
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Location: UK Other Applications are invited for a PhD project within the University of Nottingham’s Faculty of Engineering, in the Centre for Additive Manufacturing research group (CfAM
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace - In Partnership with Rolls-Royce PhD
relevant field such as engineering, computer science, or applied mathematics. Experience or interest in AI, machine learning, or digital systems is beneficial. We welcome candidates from diverse backgrounds
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Step 1: Submit your application to the QBS PhD programme via the QUB portal and enter the code QBSPGR2025/26 in the funding section: 🔗 myportal.qub.ac.uk Step 2: Email the following documents to Louise
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subwavelength features that enable tailored optical responses not found in nature—such as negative refractive index. This funded PhD studentship will develop 3D-printed optical metamaterials to sculpt ultrashort
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Start date: 29/09/2025 This is an exciting opportunity to study for a PhD funded by the EPSRC-funded EnerHy CDT and Sustainable Plastics Solutions. Offering an annual tax-free stipend of £20,780
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fees will be covered for up to three years. Eligibility Applicants must have an undergraduate or postgraduate qualification in computer science, machine learning, AI or another relevant field. Equivalent
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, supporting studies in military aircraft systems. Engaging with these facilities allows students to acquire practical skills and technical expertise, enhancing their research capabilities and employability in
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untapped potential remains in extracting value from this data. This PhD will explore advanced analytics techniques, including machine learning, digital twin modelling, time series analysis, spectral analysis
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Deadline: 30 June 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”. This position is