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Field
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may include, but are not limited to: Artificial Intelligence and Machine Learning in Art History Museums, Collections and AI 3D Scanning and Digital Heritage Extended Reality (VR, AR and Mixed Reality
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machine-learning, predictive-modelling or multivariate methods to behavioural and/or EEG data. Proficiency in R, MATLAB and Python. What we can offer In return we offer a generous pension, relocation
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ideal for a researcher with a passion for solving complex problems at the intersection of wireless communications, edge computing, and machine learning, and who is eager to translate theoretical insights
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; cost, carbon or sustainability optimisation; uncertainty and sensitivity analysis; and machine learning or AI-supported optimisation. Strong analytical and programming skills are essential. Relevant
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Python and/or C++. Demonstrable experience with machine learning frameworks (e.g., PyTorch, TensorFlow). Hands-on experience with game AI agents and/or GUI agents such as Mineflayer, Unity ML-Agents
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optimisation; uncertainty and sensitivity analysis; and machine learning or AI-supported optimisation. Strong analytical and programming skills are essential. Relevant experience may include tools and languages
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, Electrical Engineering, or a related discipline. Strong research background in one or more of: Computer Vision Machine Learning Deep Learning Video Understanding Multimodal AI Excellent programming skills in
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proving, machine learning for reasoning, or neurosymbolic AI. Desirable Application/interview Further Information Grade Grade 8 Salary £48,822 - £51,753 Work arrangement Full-time Duration Until 30th
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for: Conducting research and development on AI-based solutions for automated defect inspection and condition assessment of train components by designing and developing deep learning, computer vision, and machine
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demonstrate how innovative methodologies can generate new knowledge within art history. Relevant topics may include, but are not limited to: Artificial Intelligence and Machine Learning in Art History Museums