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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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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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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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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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Compensation $15.00 Limited Term End Date 6-30-2026 Position Summary Serves as the first contact for the department. Duties & Responsibilities Greets and directs prospective students and visitors; routes telephone calls; and schedules appointments. Coordinates daily activities of the front desk,...
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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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and machine learning applications, with an emphasis on strongly correlated condensed matter systems. This position will be for 3 months Essential Duties and Responsibilities Develop a prototype neural
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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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, 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