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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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, you will work to develop and implement machine learning approaches to identify lakes and lake drainage behaviour, and to deploy these workflows at scale. Based at Lancaster University, you will join our
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A Machine Learning Enabled Physical Layer for 6G Radio Systems School of Electrical and Electronic Engineering PhD Research Project Directly Funded UK Students Prof Timothy O'Farrel, Prof Mohammed
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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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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...
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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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, EC1Y 2AL Birmingham City University are looking to appoint a high calibre graduate (graduated within the last five years) as a Machine Learning R&D Engineer (KTP Associate). As a Machine Learning R&D
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London (UCL) has an exciting opportunity for a Lecturer in Artificial Intelligence and Machine Learning for Sustainable Construction. The post holder will be within The Bartlett School of Sustainable
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libraries. Experience with modern deep learning frameworks (e.g., PyTorch). Experience in using Large Language Models in real-world use cases. Experience in working with large datasets. Knowledge