198 machine-learning-"https:"-"https:"-"https:" Fellowship positions in United Kingdom
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relentless focus on delivering high quality teaching and learning. We are a culturally rich university with strong commitment to the public good, providing a stimulating and inclusive environment where staff
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, advanced sensing techniques, sensor and operational data fusion, data analytics, and machine learning algorithms for condition monitoring, fault diagnosis, and early fault prediction in electric vessels
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computers”(under the UKRI Guarantee scheme). Topics include: Quantum many-body dynamics Quantum algorithms Quantum-enhanced numerical methods Quantum machine learning Tensor Networks Topological order The
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good collaborative skills within a team. You may also have strong theoretical and programming background in AI, machine learning, mathematical modelling including physics-based models, and/or robot
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Digital Twin Framework for Smart and Sustainable Advanced Manufacturing Research area 3: Advanced Multifunctional Materials The ideal candidates would have a background in machine learning, manufacturing
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emerging multi-omic measurements to build and test machine-learning-based multimodal risk prediction tools. A key element of the role will be to explore how different data types and AI-derived features can
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emerging multi-omic measurements to build and test machine-learning-based multimodal risk prediction tools. A key element of the role will be to explore how different data types and AI-derived features can
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As a University of Applied Learning, the Singapore Institute of Technology (SIT) works closely with industry in its research pursuits. This position is situated within the Centre for Immersification
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computers”(under the UKRI Guarantee scheme). Topics include: - Quantum many-body dynamics - Quantum algorithms - Quantum-enhanced numerical methods - Quantum machine learning - Tensor Networks - Topological
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climate change - Computer vision, e.g., colour vision, human colour vision, colour appearance models, etc. - AI technology, e.g. statistical learning, neural network learning, deep and transfer learning