51 phd-studenship-in-computer-vision-and-machine-learning Fellowship positions at UNIVERSITY OF SOUTHAMPTON
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of this postdoctoral research position is to support the design of elastic aircraft with a combination of aerodynamic tools of different fidelity, and the development of machine learning technologies in the context
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Audition for Robots (ActivATOR)” under the direction of Dr Christine Evers. The position will be in the Vision, Learning and Control (VLC) Group, which is part of the School of Electronics and Computer
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, to develop a novel end-to-end neuromorphic design approach based on spiking neural networks (SNNs). The project aims to develop novel computing solutions for the defence and security sector, that can
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, to develop a novel end-to-end neuromorphic design approach based on spiking neural networks (SNNs). The project aims to develop novel computing solutions for the defence and security sector, that can
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PhD or equivalent professional qualifications and experience will be in distributed database systems, information retrieval, computer networking or semantic web. The post does not involve working
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smart cities. To be successful you will have: PhD in Computer Science, Data Science, Machine Learning, Electrical Engineering, or a related field with focus on speech processing, edge computing, TinyML
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manufacturing. You should have interest in or experience with data-driven methods, including machine learning, Python programming, or data curation. Regular reports of research progress are required and research
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and translation. You will be based in the School of Electronics and Computer Science (ECS), working alongside an interdisciplinary team led by Dr. Shelly Vishwakarma (s.vishwakarma@soton.ac.uk), in
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simulation tools for loads calculations; Experience with developing, training, and optimizing neural networks or other machine learning models. For this position we are targeting a salary corresponding to
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technologies and lithium-ion batteries. You will utilise our facilities to synthesis and characterise materials and devices for synchrotron experiments. We have developed cutting edge tools that include machine