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developing new methods and techniques that will improve standard ML algorithms so as to achieve good performance outside their training distribution, by treating high-dimensional problems as an explicit
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individually, make a real difference. The role To research and develop software modules, tools and API for a project that aims to create a secure decentralised data marketplace based on distributed ledger
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and its implementation in distributed systems. Main responsibilities: Research, develop, and optimise machine learning algorithms, including deep learning, for AV control and coordination. Apply multi
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include but are not limited to: programming, algorithms, software development, communications and protocols, distributed systems, databases, mobile applications, operating systems, cloud computing, web
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Particle size distribution in flue gases for carbon capture School of Mechanical, Aerospace and Civil Engineering PhD Research Project Self Funded Prof Mohamed Pourkashanian, Prof Lin Ma, Dr Kevin
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this role, you will work as part of the world-class team of researchers and software developers within the PSS team to develop all or some of firmware, software and algorithms for pulsar and fast transient
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-time reinforcement learning algorithms to personalise training difficulty for the DRUM-AI training app and help shape the future of AI-assisted rehabilitation. The post holder will be based in
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, and use smart phone apps to collect passive and active data using a prospective observational cohort study design. We will use this data to develop and validate a personalised risk prediction algorithm
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meaning from data. Designing machine learning algorithms and undertaking testing for: predictive maintenance. operational performance and cost optimization. failure prevention and timely reparation of Aids
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We are recruiting an Artist in Residence to undertake artistic research with a focus on Distributed Acoustic Sensing (DAS) technology, in the context of the recently awarded UKRI grant ‘SOUNDSCALE