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KTP Associate in Machine Learning ( Job Number: 25000811) Department of Computer Science Grade 7: - £39,105 - £43,878 per annum Fixed Term - Full Time Contract Duration: 30 months Contracted Hours
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to explore and commercialize innovations at the intersection of AI systems and machine learning, with a goal to spin out a deep-tech startup. This is a unique opportunity for someone with both technical
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at the intersection of AI systems and machine learning, with a goal to spin out a deep-tech startup. This is a unique opportunity for someone with both technical expertise and startup ambitions to be part of a venture
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combined with human support. About the role The Research Scientist in Machine Learning for Wearables will develop predictive deep learning models to assess maternal and partner health and behaviour
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Applications are invited for a University Assistant Professor in the area of ethical and trustworthy use of machine learning. This is a joint post between the Department of Engineering and the
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Accountabilities Design and implement software pipelines to deploy ML models on edge devices with real-time inference capabilities. Optimize machine learning models (e.g., quantization, pruning) for edge hardware
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adaptability of wearable and medical devices, and safer human-machine interaction. Machine Learning (ML) is an emerging technology with significant potential in integrating and embodying soft robotics
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optical communication networks and systems, as well as machine learning, computer vision and compressing digital videos. The Applied Machine Learning (AML) group is part of the Department for Artificial
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to produce cutting edge social science, computer science, and data science research that improves public policy decision making. The MDI Machine Learning Developer will engage in research, development, and
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School of Computing & Mathematical Sciences Location: Greenwich and Medway Campuses Salary: £38,249 to £44,128 Contract Type: Permanent Release Date: Friday 25 July 2025 Closing Date: Friday 08 August 2025 Interview Date: To be confirmed Reference: FES013-E We invite applications outlining...