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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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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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/d) in Energy Informatics, specifically for a DFG project in wind power forecasting using machine learning. You are passionate about applying cutting-edge information technology to solve the energy and
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engineering, computer science or a comparable subject You have good experience in Python You have basic knowledge of the theory and methods in machine learning Good language skills in German and/or English What
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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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Please note that job descriptions are not exhaustive, and you may be asked to take on additional duties that align with the key responsibilities mentioned above. We reserve the right to close the advert prior to the closing date stated should we receive a high volume of applications. It is...
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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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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