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Field
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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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contexts. They will be expected to contribute to the effective delivery of teaching, learning, and student support by: Delivering and evaluating classroom and practical teaching across modules Designing and
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, physical layer design, machine learning, and their applications to wireless communications. The successful candidate will also contribute to the formulation and submission of high-quality research
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, analytical and computer programming skills. Advantage will be given to applicants with experience in one or more of the following: signal processing, deep learning, acoustics, psychoacoustics, acoustic
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to undertake world-leading research in the design, integration and Edge-implementation/testing of multimodal machine learning models. Your experience in real-time implementation of federated AI and Edge-based
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Computer Vision and Machine Learning Specialist KTP Associate £34,000 to £38,000 per annum plus training budget of up to £4,500. Department of Computer Science TrainFX Computer Vision and Machine
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. Selection criteria: • Hold, or be near to completion of, a PhD/DPhil in biomaterials, bioengineering, biology, chemistry, nanotechnology, or related field • Experience establishing and
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as world-leading or internationally excellent. We use this expertise to teach the next generation of health professionals and research scientists. Based across King’s Denmark Hill, Guy’s, St Thomas
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. Familiarity with standard design verification (DV) procedures and continuous integration (CI) setups would be beneficial. Knowledge of machine learning workloads and the design of machine-learning accelerators
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PhD Studentship: Sleep and Circadian Rhythms in Elite Sport (Co-funded by Brighton & Hove Albion FC)
in machine learning methods for pattern recognition and prediction. An academic or practical background in sleep science and/or elite sport is highly desirable. The candidate will be embedded within