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research directions include: Develop a novel microenvironment classification algorithm by extending existing methods Model indoor air quality levels in London microenvironments by combining machine learning
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PhD at the Forefront of Computational Solid Mechanics and Machine Learning School of Mechanical, Aerospace and Civil Engineering PhD Research Project Self Funded Dr J L Curiel Sosa Application
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novel machine learning algorithms. You will be a motivated PhD in Chemistry with specialisation or equivalent research or industrial experience in digital chemistry, chemometrics and experimentation
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methods and the potential to develop pioneering reconstruction and calibration techniques involving machine learning. The PhD will prepare equally well for a career in industry and academia. The candidate
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machine learning and experimental design optimisation. Training and Career Development You will gain interdisciplinary skills in machine learning, medical image analysis, and coating design. As a PhD
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AI-based diagnostics for fleet-based condition monitoring of electric vehicle motors using machine learning frameworks (S3.5-ELE-Panagiotou) School of Electrical and Electronic Engineering PhD
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BSM processes. This will involve taking a lead role in developing dedicated software frameworks, including the implementation of machine learning techniques. A long-term attachment (6-12 months) and
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183469 – Senior Bioinformatician in Single-cell/Spatial Multi-omics and Machine Learning/Artificial Intelligence Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences
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Adversarial machine learning - Identification and prevention of cyber-physical attacks on infrastructure (S3.5-MAC-Champneys) School of Mechanical, Aerospace and Civil Engineering PhD Research
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DEFRA and MMO datasets) to build models that capture both environmental and human dimensions of offshore wind. By combining machine learning with physics-informed modelling, the project will deliver