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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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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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Machine Learning Software Engineer Machine Learning Software Engineer (Remote) *No Visa Sponsorship is available for this position. About the Cornell Lab of Ornithology The Cornell Lab of Ornithology is a
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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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qualifications required for employment as associate professor. The Computer Vision Laboratory (CVL) is looking for an assistant professor in machine learning with a focus on computational photography. CVL is a
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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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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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on computational materials science and machine learning applications, with an emphasis on strongly correlated condensed matter systems. This position will be for 3 months Essential Duties and Responsibilities
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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